allstax commited on
Commit
0b97e40
1 Parent(s): 099e61e

Upload folder using huggingface_hub

Browse files
This view is limited to 50 files because it contains too many changes.   See raw diff
Files changed (50) hide show
  1. .gitattributes +21 -0
  2. checkpoint-19200/README.md +202 -0
  3. checkpoint-19200/adapter_config.json +34 -0
  4. checkpoint-19200/adapter_model.safetensors +3 -0
  5. checkpoint-19200/rng_state.pth +3 -0
  6. checkpoint-19200/scheduler.pt +3 -0
  7. checkpoint-19200/special_tokens_map.json +34 -0
  8. checkpoint-19200/tokenizer.json +3 -0
  9. checkpoint-19200/tokenizer.model +3 -0
  10. checkpoint-19200/tokenizer_config.json +71 -0
  11. checkpoint-19200/trainer_state.json +1941 -0
  12. checkpoint-19200/training_args.bin +3 -0
  13. checkpoint-20000/README.md +202 -0
  14. checkpoint-20000/adapter_config.json +34 -0
  15. checkpoint-20000/adapter_model.safetensors +3 -0
  16. checkpoint-20000/rng_state.pth +3 -0
  17. checkpoint-20000/scheduler.pt +3 -0
  18. checkpoint-20000/special_tokens_map.json +34 -0
  19. checkpoint-20000/tokenizer.json +3 -0
  20. checkpoint-20000/tokenizer.model +3 -0
  21. checkpoint-20000/tokenizer_config.json +71 -0
  22. checkpoint-20000/trainer_state.json +2021 -0
  23. checkpoint-20000/training_args.bin +3 -0
  24. checkpoint-20800/README.md +202 -0
  25. checkpoint-20800/adapter_config.json +34 -0
  26. checkpoint-20800/adapter_model.safetensors +3 -0
  27. checkpoint-20800/rng_state.pth +3 -0
  28. checkpoint-20800/scheduler.pt +3 -0
  29. checkpoint-20800/special_tokens_map.json +34 -0
  30. checkpoint-20800/tokenizer.json +3 -0
  31. checkpoint-20800/tokenizer.model +3 -0
  32. checkpoint-20800/tokenizer_config.json +71 -0
  33. checkpoint-20800/trainer_state.json +2101 -0
  34. checkpoint-20800/training_args.bin +3 -0
  35. checkpoint-21600/README.md +202 -0
  36. checkpoint-21600/adapter_config.json +34 -0
  37. checkpoint-21600/adapter_model.safetensors +3 -0
  38. checkpoint-21600/rng_state.pth +3 -0
  39. checkpoint-21600/scheduler.pt +3 -0
  40. checkpoint-21600/special_tokens_map.json +34 -0
  41. checkpoint-21600/tokenizer.json +3 -0
  42. checkpoint-21600/tokenizer.model +3 -0
  43. checkpoint-21600/tokenizer_config.json +71 -0
  44. checkpoint-21600/trainer_state.json +2181 -0
  45. checkpoint-21600/training_args.bin +3 -0
  46. checkpoint-22400/README.md +202 -0
  47. checkpoint-22400/adapter_config.json +34 -0
  48. checkpoint-22400/adapter_model.safetensors +3 -0
  49. checkpoint-22400/rng_state.pth +3 -0
  50. checkpoint-22400/scheduler.pt +3 -0
.gitattributes CHANGED
@@ -33,3 +33,24 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
33
  *.zip filter=lfs diff=lfs merge=lfs -text
34
  *.zst filter=lfs diff=lfs merge=lfs -text
35
  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
33
  *.zip filter=lfs diff=lfs merge=lfs -text
34
  *.zst filter=lfs diff=lfs merge=lfs -text
35
  *tfevents* filter=lfs diff=lfs merge=lfs -text
36
+ checkpoint-19200/tokenizer.json filter=lfs diff=lfs merge=lfs -text
37
+ checkpoint-20000/tokenizer.json filter=lfs diff=lfs merge=lfs -text
38
+ checkpoint-20800/tokenizer.json filter=lfs diff=lfs merge=lfs -text
39
+ checkpoint-21600/tokenizer.json filter=lfs diff=lfs merge=lfs -text
40
+ checkpoint-22400/tokenizer.json filter=lfs diff=lfs merge=lfs -text
41
+ checkpoint-23200/tokenizer.json filter=lfs diff=lfs merge=lfs -text
42
+ checkpoint-24000/tokenizer.json filter=lfs diff=lfs merge=lfs -text
43
+ checkpoint-24800/tokenizer.json filter=lfs diff=lfs merge=lfs -text
44
+ checkpoint-25600/tokenizer.json filter=lfs diff=lfs merge=lfs -text
45
+ checkpoint-26400/tokenizer.json filter=lfs diff=lfs merge=lfs -text
46
+ checkpoint-27200/tokenizer.json filter=lfs diff=lfs merge=lfs -text
47
+ checkpoint-28000/tokenizer.json filter=lfs diff=lfs merge=lfs -text
48
+ checkpoint-28800/tokenizer.json filter=lfs diff=lfs merge=lfs -text
49
+ checkpoint-29600/tokenizer.json filter=lfs diff=lfs merge=lfs -text
50
+ checkpoint-30400/tokenizer.json filter=lfs diff=lfs merge=lfs -text
51
+ checkpoint-31200/tokenizer.json filter=lfs diff=lfs merge=lfs -text
52
+ checkpoint-32000/tokenizer.json filter=lfs diff=lfs merge=lfs -text
53
+ checkpoint-32800/tokenizer.json filter=lfs diff=lfs merge=lfs -text
54
+ checkpoint-33600/tokenizer.json filter=lfs diff=lfs merge=lfs -text
55
+ checkpoint-34400/tokenizer.json filter=lfs diff=lfs merge=lfs -text
56
+ checkpoint-epoch-4/tokenizer.json filter=lfs diff=lfs merge=lfs -text
checkpoint-19200/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: peft
3
+ base_model: unsloth/gemma-2b-bnb-4bit
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.10.0
checkpoint-19200/adapter_config.json ADDED
@@ -0,0 +1,34 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "unsloth/gemma-2b-bnb-4bit",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 32,
14
+ "lora_dropout": 0,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 64,
20
+ "rank_pattern": {},
21
+ "revision": "unsloth",
22
+ "target_modules": [
23
+ "v_proj",
24
+ "up_proj",
25
+ "gate_proj",
26
+ "o_proj",
27
+ "k_proj",
28
+ "down_proj",
29
+ "q_proj"
30
+ ],
31
+ "task_type": "CAUSAL_LM",
32
+ "use_dora": false,
33
+ "use_rslora": false
34
+ }
checkpoint-19200/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:285fd80afeed0c673cd24ce99ab039194c8fa120f6a1db2001e02bf9571beb6d
3
+ size 313820248
checkpoint-19200/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:7e9c79e040cd1d90c9235f5ea004ce98bb1df30785570b9fdcf2a9e29948f896
3
+ size 14244
checkpoint-19200/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a3348413c5565e84f72b5de03d822ed1866796c840ac5265b9b52f983f212aba
3
+ size 1064
checkpoint-19200/special_tokens_map.json ADDED
@@ -0,0 +1,34 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "additional_special_tokens": [
3
+ "<start_of_turn>",
4
+ "<end_of_turn>"
5
+ ],
6
+ "bos_token": {
7
+ "content": "<bos>",
8
+ "lstrip": false,
9
+ "normalized": false,
10
+ "rstrip": false,
11
+ "single_word": false
12
+ },
13
+ "eos_token": {
14
+ "content": "<eos>",
15
+ "lstrip": false,
16
+ "normalized": false,
17
+ "rstrip": false,
18
+ "single_word": false
19
+ },
20
+ "pad_token": {
21
+ "content": "<pad>",
22
+ "lstrip": false,
23
+ "normalized": false,
24
+ "rstrip": false,
25
+ "single_word": false
26
+ },
27
+ "unk_token": {
28
+ "content": "<unk>",
29
+ "lstrip": false,
30
+ "normalized": false,
31
+ "rstrip": false,
32
+ "single_word": false
33
+ }
34
+ }
checkpoint-19200/tokenizer.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:05e97791a5e007260de1db7e1692e53150e08cea481e2bf25435553380c147ee
3
+ size 17477929
checkpoint-19200/tokenizer.model ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:61a7b147390c64585d6c3543dd6fc636906c9af3865a5548f27f31aee1d4c8e2
3
+ size 4241003
checkpoint-19200/tokenizer_config.json ADDED
@@ -0,0 +1,71 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_bos_token": true,
3
+ "add_eos_token": false,
4
+ "added_tokens_decoder": {
5
+ "0": {
6
+ "content": "<pad>",
7
+ "lstrip": false,
8
+ "normalized": false,
9
+ "rstrip": false,
10
+ "single_word": false,
11
+ "special": true
12
+ },
13
+ "1": {
14
+ "content": "<eos>",
15
+ "lstrip": false,
16
+ "normalized": false,
17
+ "rstrip": false,
18
+ "single_word": false,
19
+ "special": true
20
+ },
21
+ "2": {
22
+ "content": "<bos>",
23
+ "lstrip": false,
24
+ "normalized": false,
25
+ "rstrip": false,
26
+ "single_word": false,
27
+ "special": true
28
+ },
29
+ "3": {
30
+ "content": "<unk>",
31
+ "lstrip": false,
32
+ "normalized": false,
33
+ "rstrip": false,
34
+ "single_word": false,
35
+ "special": true
36
+ },
37
+ "106": {
38
+ "content": "<start_of_turn>",
39
+ "lstrip": false,
40
+ "normalized": false,
41
+ "rstrip": false,
42
+ "single_word": false,
43
+ "special": true
44
+ },
45
+ "107": {
46
+ "content": "<end_of_turn>",
47
+ "lstrip": false,
48
+ "normalized": false,
49
+ "rstrip": false,
50
+ "single_word": false,
51
+ "special": true
52
+ }
53
+ },
54
+ "additional_special_tokens": [
55
+ "<start_of_turn>",
56
+ "<end_of_turn>"
57
+ ],
58
+ "bos_token": "<bos>",
59
+ "chat_template": "{{ bos_token }}{% if messages[0]['role'] == 'system' %}{{ raise_exception('System role not supported') }}{% endif %}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if (message['role'] == 'assistant') %}{% set role = 'model' %}{% else %}{% set role = message['role'] %}{% endif %}{{ '<start_of_turn>' + role + '\n' + message['content'] | trim + '<end_of_turn>\n' }}{% endfor %}{% if add_generation_prompt %}{{'<start_of_turn>model\n'}}{% endif %}",
60
+ "clean_up_tokenization_spaces": false,
61
+ "eos_token": "<eos>",
62
+ "legacy": null,
63
+ "model_max_length": 8192,
64
+ "pad_token": "<pad>",
65
+ "padding_side": "right",
66
+ "sp_model_kwargs": {},
67
+ "spaces_between_special_tokens": false,
68
+ "tokenizer_class": "GemmaTokenizer",
69
+ "unk_token": "<unk>",
70
+ "use_default_system_prompt": false
71
+ }
checkpoint-19200/trainer_state.json ADDED
@@ -0,0 +1,1941 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": null,
3
+ "best_model_checkpoint": null,
4
+ "epoch": 2.187161815799966,
5
+ "eval_steps": 200,
6
+ "global_step": 19200,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.02,
13
+ "grad_norm": 0.1643640249967575,
14
+ "learning_rate": 0.0001988891104338166,
15
+ "loss": 1.7673,
16
+ "step": 200
17
+ },
18
+ {
19
+ "epoch": 0.02,
20
+ "eval_bertscore": 0.7312520742416382,
21
+ "eval_loss": 1.7944419384002686,
22
+ "eval_rouge1": 0.645726048132668,
23
+ "eval_rouge2": 0.342840307585653,
24
+ "eval_rougeL": 0.5174784271125388,
25
+ "eval_rougeLsum": 0.6359911842715976,
26
+ "eval_runtime": 67.7968,
27
+ "eval_samples_per_second": 0.147,
28
+ "eval_steps_per_second": 0.074,
29
+ "step": 200
30
+ },
31
+ {
32
+ "epoch": 0.05,
33
+ "grad_norm": 0.17238478362560272,
34
+ "learning_rate": 0.00019774973651978238,
35
+ "loss": 1.6985,
36
+ "step": 400
37
+ },
38
+ {
39
+ "epoch": 0.05,
40
+ "eval_bertscore": 0.733666718006134,
41
+ "eval_loss": 1.7791178226470947,
42
+ "eval_rouge1": 0.6540909153028596,
43
+ "eval_rouge2": 0.3548819059818129,
44
+ "eval_rougeL": 0.527257232694246,
45
+ "eval_rougeLsum": 0.6442799950994005,
46
+ "eval_runtime": 15.1267,
47
+ "eval_samples_per_second": 0.661,
48
+ "eval_steps_per_second": 0.331,
49
+ "step": 400
50
+ },
51
+ {
52
+ "epoch": 0.07,
53
+ "grad_norm": 0.19368696212768555,
54
+ "learning_rate": 0.00019661036260574814,
55
+ "loss": 1.6962,
56
+ "step": 600
57
+ },
58
+ {
59
+ "epoch": 0.07,
60
+ "eval_bertscore": 0.7339462041854858,
61
+ "eval_loss": 1.7609882354736328,
62
+ "eval_rouge1": 0.6384337329686338,
63
+ "eval_rouge2": 0.3415514270662107,
64
+ "eval_rougeL": 0.51206080148464,
65
+ "eval_rougeLsum": 0.6261968614666548,
66
+ "eval_runtime": 15.2068,
67
+ "eval_samples_per_second": 0.658,
68
+ "eval_steps_per_second": 0.329,
69
+ "step": 600
70
+ },
71
+ {
72
+ "epoch": 0.09,
73
+ "grad_norm": 0.18629203736782074,
74
+ "learning_rate": 0.00019547098869171392,
75
+ "loss": 1.6825,
76
+ "step": 800
77
+ },
78
+ {
79
+ "epoch": 0.09,
80
+ "eval_bertscore": 0.7363594174385071,
81
+ "eval_loss": 1.7610784769058228,
82
+ "eval_rouge1": 0.6461624591922237,
83
+ "eval_rouge2": 0.3477371388439609,
84
+ "eval_rougeL": 0.5187429174752844,
85
+ "eval_rougeLsum": 0.6361089823008282,
86
+ "eval_runtime": 15.173,
87
+ "eval_samples_per_second": 0.659,
88
+ "eval_steps_per_second": 0.33,
89
+ "step": 800
90
+ },
91
+ {
92
+ "epoch": 0.11,
93
+ "grad_norm": 0.1799013316631317,
94
+ "learning_rate": 0.00019433161477767967,
95
+ "loss": 1.6848,
96
+ "step": 1000
97
+ },
98
+ {
99
+ "epoch": 0.11,
100
+ "eval_bertscore": 0.7334067225456238,
101
+ "eval_loss": 1.7576347589492798,
102
+ "eval_rouge1": 0.6345119236349537,
103
+ "eval_rouge2": 0.3422519149071803,
104
+ "eval_rougeL": 0.5111983101326238,
105
+ "eval_rougeLsum": 0.6244653120436832,
106
+ "eval_runtime": 15.2847,
107
+ "eval_samples_per_second": 0.654,
108
+ "eval_steps_per_second": 0.327,
109
+ "step": 1000
110
+ },
111
+ {
112
+ "epoch": 0.14,
113
+ "grad_norm": 0.22036150097846985,
114
+ "learning_rate": 0.00019319224086364545,
115
+ "loss": 1.6714,
116
+ "step": 1200
117
+ },
118
+ {
119
+ "epoch": 0.14,
120
+ "eval_bertscore": 0.7323788404464722,
121
+ "eval_loss": 1.7521806955337524,
122
+ "eval_rouge1": 0.6452540184557478,
123
+ "eval_rouge2": 0.3465145726476423,
124
+ "eval_rougeL": 0.516711757588783,
125
+ "eval_rougeLsum": 0.6341049885677059,
126
+ "eval_runtime": 15.1247,
127
+ "eval_samples_per_second": 0.661,
128
+ "eval_steps_per_second": 0.331,
129
+ "step": 1200
130
+ },
131
+ {
132
+ "epoch": 0.16,
133
+ "grad_norm": 0.21381086111068726,
134
+ "learning_rate": 0.0001920528669496112,
135
+ "loss": 1.6669,
136
+ "step": 1400
137
+ },
138
+ {
139
+ "epoch": 0.16,
140
+ "eval_bertscore": 0.7313202619552612,
141
+ "eval_loss": 1.7520482540130615,
142
+ "eval_rouge1": 0.6397526546254797,
143
+ "eval_rouge2": 0.3452671288110514,
144
+ "eval_rougeL": 0.5176580626678706,
145
+ "eval_rougeLsum": 0.6296746647539768,
146
+ "eval_runtime": 15.183,
147
+ "eval_samples_per_second": 0.659,
148
+ "eval_steps_per_second": 0.329,
149
+ "step": 1400
150
+ },
151
+ {
152
+ "epoch": 0.18,
153
+ "grad_norm": 0.20332874357700348,
154
+ "learning_rate": 0.00019091349303557696,
155
+ "loss": 1.671,
156
+ "step": 1600
157
+ },
158
+ {
159
+ "epoch": 0.18,
160
+ "eval_bertscore": 0.7349230647087097,
161
+ "eval_loss": 1.7473630905151367,
162
+ "eval_rouge1": 0.637439872504459,
163
+ "eval_rouge2": 0.34307164454056094,
164
+ "eval_rougeL": 0.5129717676228565,
165
+ "eval_rougeLsum": 0.6272190896182391,
166
+ "eval_runtime": 15.5672,
167
+ "eval_samples_per_second": 0.642,
168
+ "eval_steps_per_second": 0.321,
169
+ "step": 1600
170
+ },
171
+ {
172
+ "epoch": 0.21,
173
+ "grad_norm": 0.2025599479675293,
174
+ "learning_rate": 0.00018977411912154274,
175
+ "loss": 1.6721,
176
+ "step": 1800
177
+ },
178
+ {
179
+ "epoch": 0.21,
180
+ "eval_bertscore": 0.7357184290885925,
181
+ "eval_loss": 1.7516342401504517,
182
+ "eval_rouge1": 0.6387615819926658,
183
+ "eval_rouge2": 0.34366787517105574,
184
+ "eval_rougeL": 0.5129026911770751,
185
+ "eval_rougeLsum": 0.6289314118258257,
186
+ "eval_runtime": 15.9574,
187
+ "eval_samples_per_second": 0.627,
188
+ "eval_steps_per_second": 0.313,
189
+ "step": 1800
190
+ },
191
+ {
192
+ "epoch": 0.23,
193
+ "grad_norm": 0.20457112789154053,
194
+ "learning_rate": 0.0001886347452075085,
195
+ "loss": 1.671,
196
+ "step": 2000
197
+ },
198
+ {
199
+ "epoch": 0.23,
200
+ "eval_bertscore": 0.733718752861023,
201
+ "eval_loss": 1.7501707077026367,
202
+ "eval_rouge1": 0.6346207681220664,
203
+ "eval_rouge2": 0.33748369437614106,
204
+ "eval_rougeL": 0.5085159047705141,
205
+ "eval_rougeLsum": 0.6239953154441167,
206
+ "eval_runtime": 15.0863,
207
+ "eval_samples_per_second": 0.663,
208
+ "eval_steps_per_second": 0.331,
209
+ "step": 2000
210
+ },
211
+ {
212
+ "epoch": 0.25,
213
+ "grad_norm": 0.22552740573883057,
214
+ "learning_rate": 0.00018749537129347424,
215
+ "loss": 1.6496,
216
+ "step": 2200
217
+ },
218
+ {
219
+ "epoch": 0.25,
220
+ "eval_bertscore": 0.7368552684783936,
221
+ "eval_loss": 1.7437107563018799,
222
+ "eval_rouge1": 0.6490756387878311,
223
+ "eval_rouge2": 0.3448817738175175,
224
+ "eval_rougeL": 0.5235187045706321,
225
+ "eval_rougeLsum": 0.6377780857890332,
226
+ "eval_runtime": 15.07,
227
+ "eval_samples_per_second": 0.664,
228
+ "eval_steps_per_second": 0.332,
229
+ "step": 2200
230
+ },
231
+ {
232
+ "epoch": 0.27,
233
+ "grad_norm": 0.22573673725128174,
234
+ "learning_rate": 0.00018635599737944,
235
+ "loss": 1.6629,
236
+ "step": 2400
237
+ },
238
+ {
239
+ "epoch": 0.27,
240
+ "eval_bertscore": 0.7314499616622925,
241
+ "eval_loss": 1.7462828159332275,
242
+ "eval_rouge1": 0.6511482369678803,
243
+ "eval_rouge2": 0.34632544827771805,
244
+ "eval_rougeL": 0.5212417191003778,
245
+ "eval_rougeLsum": 0.6415391907940229,
246
+ "eval_runtime": 15.2078,
247
+ "eval_samples_per_second": 0.658,
248
+ "eval_steps_per_second": 0.329,
249
+ "step": 2400
250
+ },
251
+ {
252
+ "epoch": 0.3,
253
+ "grad_norm": 0.26426687836647034,
254
+ "learning_rate": 0.00018521662346540575,
255
+ "loss": 1.6644,
256
+ "step": 2600
257
+ },
258
+ {
259
+ "epoch": 0.3,
260
+ "eval_bertscore": 0.7363359928131104,
261
+ "eval_loss": 1.7505037784576416,
262
+ "eval_rouge1": 0.6498296552335481,
263
+ "eval_rouge2": 0.34873833589761183,
264
+ "eval_rougeL": 0.5194028620820592,
265
+ "eval_rougeLsum": 0.6404603087578984,
266
+ "eval_runtime": 14.8403,
267
+ "eval_samples_per_second": 0.674,
268
+ "eval_steps_per_second": 0.337,
269
+ "step": 2600
270
+ },
271
+ {
272
+ "epoch": 0.32,
273
+ "grad_norm": 0.20142091810703278,
274
+ "learning_rate": 0.00018407724955137153,
275
+ "loss": 1.6535,
276
+ "step": 2800
277
+ },
278
+ {
279
+ "epoch": 0.32,
280
+ "eval_bertscore": 0.7304679155349731,
281
+ "eval_loss": 1.7511039972305298,
282
+ "eval_rouge1": 0.6475130585388738,
283
+ "eval_rouge2": 0.34648331046897884,
284
+ "eval_rougeL": 0.5218042284020985,
285
+ "eval_rougeLsum": 0.6382749834402862,
286
+ "eval_runtime": 15.0162,
287
+ "eval_samples_per_second": 0.666,
288
+ "eval_steps_per_second": 0.333,
289
+ "step": 2800
290
+ },
291
+ {
292
+ "epoch": 0.34,
293
+ "grad_norm": 0.23283220827579498,
294
+ "learning_rate": 0.00018293787563733728,
295
+ "loss": 1.6477,
296
+ "step": 3000
297
+ },
298
+ {
299
+ "epoch": 0.34,
300
+ "eval_bertscore": 0.7327049374580383,
301
+ "eval_loss": 1.7461665868759155,
302
+ "eval_rouge1": 0.6309349586871908,
303
+ "eval_rouge2": 0.3387882478990309,
304
+ "eval_rougeL": 0.5042059192403674,
305
+ "eval_rougeLsum": 0.6210432469674847,
306
+ "eval_runtime": 15.463,
307
+ "eval_samples_per_second": 0.647,
308
+ "eval_steps_per_second": 0.323,
309
+ "step": 3000
310
+ },
311
+ {
312
+ "epoch": 0.36,
313
+ "grad_norm": 0.21316750347614288,
314
+ "learning_rate": 0.00018179850172330306,
315
+ "loss": 1.6614,
316
+ "step": 3200
317
+ },
318
+ {
319
+ "epoch": 0.36,
320
+ "eval_bertscore": 0.7314620018005371,
321
+ "eval_loss": 1.7468239068984985,
322
+ "eval_rouge1": 0.6480904534152265,
323
+ "eval_rouge2": 0.3479530168963481,
324
+ "eval_rougeL": 0.5193148273848067,
325
+ "eval_rougeLsum": 0.6366010767207634,
326
+ "eval_runtime": 15.0381,
327
+ "eval_samples_per_second": 0.665,
328
+ "eval_steps_per_second": 0.332,
329
+ "step": 3200
330
+ },
331
+ {
332
+ "epoch": 0.39,
333
+ "grad_norm": 0.26080408692359924,
334
+ "learning_rate": 0.00018065912780926882,
335
+ "loss": 1.6591,
336
+ "step": 3400
337
+ },
338
+ {
339
+ "epoch": 0.39,
340
+ "eval_bertscore": 0.7327477335929871,
341
+ "eval_loss": 1.7442594766616821,
342
+ "eval_rouge1": 0.6424613378037144,
343
+ "eval_rouge2": 0.34731770322974903,
344
+ "eval_rougeL": 0.5160705879794565,
345
+ "eval_rougeLsum": 0.6327006420281607,
346
+ "eval_runtime": 15.5373,
347
+ "eval_samples_per_second": 0.644,
348
+ "eval_steps_per_second": 0.322,
349
+ "step": 3400
350
+ },
351
+ {
352
+ "epoch": 0.41,
353
+ "grad_norm": 0.23274216055870056,
354
+ "learning_rate": 0.0001795197538952346,
355
+ "loss": 1.6613,
356
+ "step": 3600
357
+ },
358
+ {
359
+ "epoch": 0.41,
360
+ "eval_bertscore": 0.736956000328064,
361
+ "eval_loss": 1.7429373264312744,
362
+ "eval_rouge1": 0.6514574160666677,
363
+ "eval_rouge2": 0.3556199242231646,
364
+ "eval_rougeL": 0.5249726237675663,
365
+ "eval_rougeLsum": 0.6406261097623661,
366
+ "eval_runtime": 14.9415,
367
+ "eval_samples_per_second": 0.669,
368
+ "eval_steps_per_second": 0.335,
369
+ "step": 3600
370
+ },
371
+ {
372
+ "epoch": 0.43,
373
+ "grad_norm": 0.23616766929626465,
374
+ "learning_rate": 0.00017838037998120035,
375
+ "loss": 1.6479,
376
+ "step": 3800
377
+ },
378
+ {
379
+ "epoch": 0.43,
380
+ "eval_bertscore": 0.7349627614021301,
381
+ "eval_loss": 1.7420669794082642,
382
+ "eval_rouge1": 0.655851684949526,
383
+ "eval_rouge2": 0.35254590691865084,
384
+ "eval_rougeL": 0.5248980956621441,
385
+ "eval_rougeLsum": 0.6449637270581419,
386
+ "eval_runtime": 15.4178,
387
+ "eval_samples_per_second": 0.649,
388
+ "eval_steps_per_second": 0.324,
389
+ "step": 3800
390
+ },
391
+ {
392
+ "epoch": 0.46,
393
+ "grad_norm": 0.23260319232940674,
394
+ "learning_rate": 0.0001772410060671661,
395
+ "loss": 1.6569,
396
+ "step": 4000
397
+ },
398
+ {
399
+ "epoch": 0.46,
400
+ "eval_bertscore": 0.7332885265350342,
401
+ "eval_loss": 1.7401313781738281,
402
+ "eval_rouge1": 0.6669483634140105,
403
+ "eval_rouge2": 0.35873988835161297,
404
+ "eval_rougeL": 0.5343868725007427,
405
+ "eval_rougeLsum": 0.6555353134690931,
406
+ "eval_runtime": 15.0822,
407
+ "eval_samples_per_second": 0.663,
408
+ "eval_steps_per_second": 0.332,
409
+ "step": 4000
410
+ },
411
+ {
412
+ "epoch": 0.48,
413
+ "grad_norm": 0.2366473525762558,
414
+ "learning_rate": 0.00017610163215313186,
415
+ "loss": 1.6599,
416
+ "step": 4200
417
+ },
418
+ {
419
+ "epoch": 0.48,
420
+ "eval_bertscore": 0.7335314750671387,
421
+ "eval_loss": 1.7385823726654053,
422
+ "eval_rouge1": 0.6559297063578133,
423
+ "eval_rouge2": 0.35483499789990636,
424
+ "eval_rougeL": 0.5297939800986089,
425
+ "eval_rougeLsum": 0.6454544372491222,
426
+ "eval_runtime": 15.1029,
427
+ "eval_samples_per_second": 0.662,
428
+ "eval_steps_per_second": 0.331,
429
+ "step": 4200
430
+ },
431
+ {
432
+ "epoch": 0.5,
433
+ "grad_norm": 0.20628753304481506,
434
+ "learning_rate": 0.0001749622582390976,
435
+ "loss": 1.6454,
436
+ "step": 4400
437
+ },
438
+ {
439
+ "epoch": 0.5,
440
+ "eval_bertscore": 0.7342795133590698,
441
+ "eval_loss": 1.7422058582305908,
442
+ "eval_rouge1": 0.660746519614568,
443
+ "eval_rouge2": 0.3633965895561597,
444
+ "eval_rougeL": 0.5369036980876734,
445
+ "eval_rougeLsum": 0.650338328328998,
446
+ "eval_runtime": 15.4434,
447
+ "eval_samples_per_second": 0.648,
448
+ "eval_steps_per_second": 0.324,
449
+ "step": 4400
450
+ },
451
+ {
452
+ "epoch": 0.52,
453
+ "grad_norm": 0.2239149957895279,
454
+ "learning_rate": 0.0001738228843250634,
455
+ "loss": 1.6594,
456
+ "step": 4600
457
+ },
458
+ {
459
+ "epoch": 0.52,
460
+ "eval_bertscore": 0.7313543558120728,
461
+ "eval_loss": 1.740854263305664,
462
+ "eval_rouge1": 0.6591645132619427,
463
+ "eval_rouge2": 0.35766117432431743,
464
+ "eval_rougeL": 0.532710255034635,
465
+ "eval_rougeLsum": 0.6479428185884644,
466
+ "eval_runtime": 14.9436,
467
+ "eval_samples_per_second": 0.669,
468
+ "eval_steps_per_second": 0.335,
469
+ "step": 4600
470
+ },
471
+ {
472
+ "epoch": 0.55,
473
+ "grad_norm": 0.24808338284492493,
474
+ "learning_rate": 0.00017268351041102914,
475
+ "loss": 1.6604,
476
+ "step": 4800
477
+ },
478
+ {
479
+ "epoch": 0.55,
480
+ "eval_bertscore": 0.7333321571350098,
481
+ "eval_loss": 1.7385585308074951,
482
+ "eval_rouge1": 0.6532115808232871,
483
+ "eval_rouge2": 0.35333788022501567,
484
+ "eval_rougeL": 0.5284071547874328,
485
+ "eval_rougeLsum": 0.6410472452797623,
486
+ "eval_runtime": 15.0277,
487
+ "eval_samples_per_second": 0.665,
488
+ "eval_steps_per_second": 0.333,
489
+ "step": 4800
490
+ },
491
+ {
492
+ "epoch": 0.57,
493
+ "grad_norm": 0.2555364966392517,
494
+ "learning_rate": 0.0001715441364969949,
495
+ "loss": 1.6493,
496
+ "step": 5000
497
+ },
498
+ {
499
+ "epoch": 0.57,
500
+ "eval_bertscore": 0.7318152189254761,
501
+ "eval_loss": 1.7357494831085205,
502
+ "eval_rouge1": 0.6476755890502586,
503
+ "eval_rouge2": 0.35312778275949164,
504
+ "eval_rougeL": 0.5227601228049905,
505
+ "eval_rougeLsum": 0.6371331138372852,
506
+ "eval_runtime": 14.8807,
507
+ "eval_samples_per_second": 0.672,
508
+ "eval_steps_per_second": 0.336,
509
+ "step": 5000
510
+ },
511
+ {
512
+ "epoch": 0.59,
513
+ "grad_norm": 0.21518155932426453,
514
+ "learning_rate": 0.00017040476258296068,
515
+ "loss": 1.644,
516
+ "step": 5200
517
+ },
518
+ {
519
+ "epoch": 0.59,
520
+ "eval_bertscore": 0.734805703163147,
521
+ "eval_loss": 1.74032723903656,
522
+ "eval_rouge1": 0.6476813733451636,
523
+ "eval_rouge2": 0.3509259728617576,
524
+ "eval_rougeL": 0.5221334872800274,
525
+ "eval_rougeLsum": 0.636892384667733,
526
+ "eval_runtime": 15.1271,
527
+ "eval_samples_per_second": 0.661,
528
+ "eval_steps_per_second": 0.331,
529
+ "step": 5200
530
+ },
531
+ {
532
+ "epoch": 0.62,
533
+ "grad_norm": 0.26086658239364624,
534
+ "learning_rate": 0.00016926538866892643,
535
+ "loss": 1.6449,
536
+ "step": 5400
537
+ },
538
+ {
539
+ "epoch": 0.62,
540
+ "eval_bertscore": 0.7339995503425598,
541
+ "eval_loss": 1.7338205575942993,
542
+ "eval_rouge1": 0.6416889902864902,
543
+ "eval_rouge2": 0.3479045880347737,
544
+ "eval_rougeL": 0.5160577838468976,
545
+ "eval_rougeLsum": 0.6317983411796093,
546
+ "eval_runtime": 14.9992,
547
+ "eval_samples_per_second": 0.667,
548
+ "eval_steps_per_second": 0.333,
549
+ "step": 5400
550
+ },
551
+ {
552
+ "epoch": 0.64,
553
+ "grad_norm": 0.25449469685554504,
554
+ "learning_rate": 0.0001681260147548922,
555
+ "loss": 1.6299,
556
+ "step": 5600
557
+ },
558
+ {
559
+ "epoch": 0.64,
560
+ "eval_bertscore": 0.7306328415870667,
561
+ "eval_loss": 1.7369228601455688,
562
+ "eval_rouge1": 0.6390760905985684,
563
+ "eval_rouge2": 0.3409328272828699,
564
+ "eval_rougeL": 0.5111832543685331,
565
+ "eval_rougeLsum": 0.6285753423407665,
566
+ "eval_runtime": 15.483,
567
+ "eval_samples_per_second": 0.646,
568
+ "eval_steps_per_second": 0.323,
569
+ "step": 5600
570
+ },
571
+ {
572
+ "epoch": 0.66,
573
+ "grad_norm": 0.24706102907657623,
574
+ "learning_rate": 0.00016698664084085796,
575
+ "loss": 1.6374,
576
+ "step": 5800
577
+ },
578
+ {
579
+ "epoch": 0.66,
580
+ "eval_bertscore": 0.732075572013855,
581
+ "eval_loss": 1.7343876361846924,
582
+ "eval_rouge1": 0.6378821977913272,
583
+ "eval_rouge2": 0.34619427775171585,
584
+ "eval_rougeL": 0.5120186953041237,
585
+ "eval_rougeLsum": 0.6284056323839109,
586
+ "eval_runtime": 15.7341,
587
+ "eval_samples_per_second": 0.636,
588
+ "eval_steps_per_second": 0.318,
589
+ "step": 5800
590
+ },
591
+ {
592
+ "epoch": 0.68,
593
+ "grad_norm": 0.24373260140419006,
594
+ "learning_rate": 0.00016584726692682372,
595
+ "loss": 1.6427,
596
+ "step": 6000
597
+ },
598
+ {
599
+ "epoch": 0.68,
600
+ "eval_bertscore": 0.7350374460220337,
601
+ "eval_loss": 1.729591965675354,
602
+ "eval_rouge1": 0.6516545226356616,
603
+ "eval_rouge2": 0.35485762033878543,
604
+ "eval_rougeL": 0.5249054193354852,
605
+ "eval_rougeLsum": 0.6411016821651583,
606
+ "eval_runtime": 15.5199,
607
+ "eval_samples_per_second": 0.644,
608
+ "eval_steps_per_second": 0.322,
609
+ "step": 6000
610
+ },
611
+ {
612
+ "epoch": 0.71,
613
+ "grad_norm": 0.24616578221321106,
614
+ "learning_rate": 0.0001647078930127895,
615
+ "loss": 1.6296,
616
+ "step": 6200
617
+ },
618
+ {
619
+ "epoch": 0.71,
620
+ "eval_bertscore": 0.7335461378097534,
621
+ "eval_loss": 1.7302274703979492,
622
+ "eval_rouge1": 0.6531411706717427,
623
+ "eval_rouge2": 0.35003053174601517,
624
+ "eval_rougeL": 0.5212483686089053,
625
+ "eval_rougeLsum": 0.6438454124825417,
626
+ "eval_runtime": 15.3058,
627
+ "eval_samples_per_second": 0.653,
628
+ "eval_steps_per_second": 0.327,
629
+ "step": 6200
630
+ },
631
+ {
632
+ "epoch": 0.73,
633
+ "grad_norm": 0.24500492215156555,
634
+ "learning_rate": 0.00016356851909875522,
635
+ "loss": 1.6251,
636
+ "step": 6400
637
+ },
638
+ {
639
+ "epoch": 0.73,
640
+ "eval_bertscore": 0.7347471714019775,
641
+ "eval_loss": 1.7292228937149048,
642
+ "eval_rouge1": 0.6565322485502556,
643
+ "eval_rouge2": 0.35887540291607073,
644
+ "eval_rougeL": 0.5284326132878907,
645
+ "eval_rougeLsum": 0.6469750895866724,
646
+ "eval_runtime": 14.9708,
647
+ "eval_samples_per_second": 0.668,
648
+ "eval_steps_per_second": 0.334,
649
+ "step": 6400
650
+ },
651
+ {
652
+ "epoch": 0.75,
653
+ "grad_norm": 0.26575228571891785,
654
+ "learning_rate": 0.000162429145184721,
655
+ "loss": 1.6389,
656
+ "step": 6600
657
+ },
658
+ {
659
+ "epoch": 0.75,
660
+ "eval_bertscore": 0.7319897413253784,
661
+ "eval_loss": 1.7287580966949463,
662
+ "eval_rouge1": 0.6458608801881298,
663
+ "eval_rouge2": 0.3503480901452204,
664
+ "eval_rougeL": 0.519626708150005,
665
+ "eval_rougeLsum": 0.6362405734928169,
666
+ "eval_runtime": 15.3509,
667
+ "eval_samples_per_second": 0.651,
668
+ "eval_steps_per_second": 0.326,
669
+ "step": 6600
670
+ },
671
+ {
672
+ "epoch": 0.77,
673
+ "grad_norm": 0.27144965529441833,
674
+ "learning_rate": 0.00016128977127068676,
675
+ "loss": 1.6476,
676
+ "step": 6800
677
+ },
678
+ {
679
+ "epoch": 0.77,
680
+ "eval_bertscore": 0.7392772436141968,
681
+ "eval_loss": 1.7257907390594482,
682
+ "eval_rouge1": 0.6543238897579965,
683
+ "eval_rouge2": 0.3606726049451984,
684
+ "eval_rougeL": 0.5317585887753791,
685
+ "eval_rougeLsum": 0.6452028420624081,
686
+ "eval_runtime": 15.0268,
687
+ "eval_samples_per_second": 0.665,
688
+ "eval_steps_per_second": 0.333,
689
+ "step": 6800
690
+ },
691
+ {
692
+ "epoch": 0.8,
693
+ "grad_norm": 0.2579711079597473,
694
+ "learning_rate": 0.00016015039735665254,
695
+ "loss": 1.6316,
696
+ "step": 7000
697
+ },
698
+ {
699
+ "epoch": 0.8,
700
+ "eval_bertscore": 0.7375612854957581,
701
+ "eval_loss": 1.7296981811523438,
702
+ "eval_rouge1": 0.658906725408624,
703
+ "eval_rouge2": 0.35825094165644866,
704
+ "eval_rougeL": 0.5323299193377959,
705
+ "eval_rougeLsum": 0.6500364347290426,
706
+ "eval_runtime": 14.9244,
707
+ "eval_samples_per_second": 0.67,
708
+ "eval_steps_per_second": 0.335,
709
+ "step": 7000
710
+ },
711
+ {
712
+ "epoch": 0.82,
713
+ "grad_norm": 0.2589207589626312,
714
+ "learning_rate": 0.0001590110234426183,
715
+ "loss": 1.6432,
716
+ "step": 7200
717
+ },
718
+ {
719
+ "epoch": 0.82,
720
+ "eval_bertscore": 0.735145092010498,
721
+ "eval_loss": 1.72720205783844,
722
+ "eval_rouge1": 0.6678646250245518,
723
+ "eval_rouge2": 0.36332843150846983,
724
+ "eval_rougeL": 0.537576430733886,
725
+ "eval_rougeLsum": 0.6579789388660506,
726
+ "eval_runtime": 14.9067,
727
+ "eval_samples_per_second": 0.671,
728
+ "eval_steps_per_second": 0.335,
729
+ "step": 7200
730
+ },
731
+ {
732
+ "epoch": 0.84,
733
+ "grad_norm": 0.26652559638023376,
734
+ "learning_rate": 0.00015787164952858404,
735
+ "loss": 1.6488,
736
+ "step": 7400
737
+ },
738
+ {
739
+ "epoch": 0.84,
740
+ "eval_bertscore": 0.7320755124092102,
741
+ "eval_loss": 1.7282931804656982,
742
+ "eval_rouge1": 0.6325633297780734,
743
+ "eval_rouge2": 0.34505856555703185,
744
+ "eval_rougeL": 0.5100006743383693,
745
+ "eval_rougeLsum": 0.6230385336341938,
746
+ "eval_runtime": 14.9075,
747
+ "eval_samples_per_second": 0.671,
748
+ "eval_steps_per_second": 0.335,
749
+ "step": 7400
750
+ },
751
+ {
752
+ "epoch": 0.87,
753
+ "grad_norm": 0.27353721857070923,
754
+ "learning_rate": 0.00015673227561454982,
755
+ "loss": 1.6486,
756
+ "step": 7600
757
+ },
758
+ {
759
+ "epoch": 0.87,
760
+ "eval_bertscore": 0.7367390394210815,
761
+ "eval_loss": 1.7290785312652588,
762
+ "eval_rouge1": 0.639487116874423,
763
+ "eval_rouge2": 0.3466574229736927,
764
+ "eval_rougeL": 0.515038120249177,
765
+ "eval_rougeLsum": 0.6301157215372983,
766
+ "eval_runtime": 15.0876,
767
+ "eval_samples_per_second": 0.663,
768
+ "eval_steps_per_second": 0.331,
769
+ "step": 7600
770
+ },
771
+ {
772
+ "epoch": 0.89,
773
+ "grad_norm": 0.24777938425540924,
774
+ "learning_rate": 0.00015559290170051558,
775
+ "loss": 1.6271,
776
+ "step": 7800
777
+ },
778
+ {
779
+ "epoch": 0.89,
780
+ "eval_bertscore": 0.735866904258728,
781
+ "eval_loss": 1.7264015674591064,
782
+ "eval_rouge1": 0.64939597901302,
783
+ "eval_rouge2": 0.3554282813944538,
784
+ "eval_rougeL": 0.5247953329477759,
785
+ "eval_rougeLsum": 0.6405524812915908,
786
+ "eval_runtime": 14.8892,
787
+ "eval_samples_per_second": 0.672,
788
+ "eval_steps_per_second": 0.336,
789
+ "step": 7800
790
+ },
791
+ {
792
+ "epoch": 0.91,
793
+ "grad_norm": 0.2703794538974762,
794
+ "learning_rate": 0.00015445352778648136,
795
+ "loss": 1.6415,
796
+ "step": 8000
797
+ },
798
+ {
799
+ "epoch": 0.91,
800
+ "eval_bertscore": 0.7325771450996399,
801
+ "eval_loss": 1.7271970510482788,
802
+ "eval_rouge1": 0.6659432894288253,
803
+ "eval_rouge2": 0.35962933912652617,
804
+ "eval_rougeL": 0.5385420432813512,
805
+ "eval_rougeLsum": 0.6557027031484046,
806
+ "eval_runtime": 14.8319,
807
+ "eval_samples_per_second": 0.674,
808
+ "eval_steps_per_second": 0.337,
809
+ "step": 8000
810
+ },
811
+ {
812
+ "epoch": 0.93,
813
+ "grad_norm": 0.28753793239593506,
814
+ "learning_rate": 0.0001533141538724471,
815
+ "loss": 1.6239,
816
+ "step": 8200
817
+ },
818
+ {
819
+ "epoch": 0.93,
820
+ "eval_bertscore": 0.7350013852119446,
821
+ "eval_loss": 1.7266199588775635,
822
+ "eval_rouge1": 0.6549282561414593,
823
+ "eval_rouge2": 0.35694530595734475,
824
+ "eval_rougeL": 0.5301601006964574,
825
+ "eval_rougeLsum": 0.6441779306137909,
826
+ "eval_runtime": 14.9005,
827
+ "eval_samples_per_second": 0.671,
828
+ "eval_steps_per_second": 0.336,
829
+ "step": 8200
830
+ },
831
+ {
832
+ "epoch": 0.96,
833
+ "grad_norm": 0.23870150744915009,
834
+ "learning_rate": 0.00015217477995841286,
835
+ "loss": 1.6293,
836
+ "step": 8400
837
+ },
838
+ {
839
+ "epoch": 0.96,
840
+ "eval_bertscore": 0.7271261811256409,
841
+ "eval_loss": 1.7256368398666382,
842
+ "eval_rouge1": 0.6515513829901936,
843
+ "eval_rouge2": 0.35217616104918836,
844
+ "eval_rougeL": 0.5236553509227138,
845
+ "eval_rougeLsum": 0.6411473505324752,
846
+ "eval_runtime": 14.9938,
847
+ "eval_samples_per_second": 0.667,
848
+ "eval_steps_per_second": 0.333,
849
+ "step": 8400
850
+ },
851
+ {
852
+ "epoch": 0.98,
853
+ "grad_norm": 0.28276997804641724,
854
+ "learning_rate": 0.00015103540604437861,
855
+ "loss": 1.6242,
856
+ "step": 8600
857
+ },
858
+ {
859
+ "epoch": 0.98,
860
+ "eval_bertscore": 0.7347334027290344,
861
+ "eval_loss": 1.717627763748169,
862
+ "eval_rouge1": 0.6350112495847634,
863
+ "eval_rouge2": 0.3477570751550898,
864
+ "eval_rougeL": 0.5146616989899861,
865
+ "eval_rougeLsum": 0.6246669376525157,
866
+ "eval_runtime": 15.7032,
867
+ "eval_samples_per_second": 0.637,
868
+ "eval_steps_per_second": 0.318,
869
+ "step": 8600
870
+ },
871
+ {
872
+ "epoch": 1.0,
873
+ "grad_norm": 0.24915842711925507,
874
+ "learning_rate": 0.00014989603213034437,
875
+ "loss": 1.6245,
876
+ "step": 8800
877
+ },
878
+ {
879
+ "epoch": 1.0,
880
+ "eval_bertscore": 0.7313701510429382,
881
+ "eval_loss": 1.7292964458465576,
882
+ "eval_rouge1": 0.6479528105367669,
883
+ "eval_rouge2": 0.35020983244262877,
884
+ "eval_rougeL": 0.5200907337780047,
885
+ "eval_rougeLsum": 0.6372896614836894,
886
+ "eval_runtime": 15.0043,
887
+ "eval_samples_per_second": 0.666,
888
+ "eval_steps_per_second": 0.333,
889
+ "step": 8800
890
+ },
891
+ {
892
+ "epoch": 1.03,
893
+ "grad_norm": 0.24036027491092682,
894
+ "learning_rate": 0.00014875665821631015,
895
+ "loss": 1.5364,
896
+ "step": 9000
897
+ },
898
+ {
899
+ "epoch": 1.03,
900
+ "eval_bertscore": 0.7327737808227539,
901
+ "eval_loss": 1.7339435815811157,
902
+ "eval_rouge1": 0.6568524178922349,
903
+ "eval_rouge2": 0.35560270713543163,
904
+ "eval_rougeL": 0.5310443670833082,
905
+ "eval_rougeLsum": 0.6480993679097387,
906
+ "eval_runtime": 14.9303,
907
+ "eval_samples_per_second": 0.67,
908
+ "eval_steps_per_second": 0.335,
909
+ "step": 9000
910
+ },
911
+ {
912
+ "epoch": 1.05,
913
+ "grad_norm": 0.2729027271270752,
914
+ "learning_rate": 0.0001476172843022759,
915
+ "loss": 1.5182,
916
+ "step": 9200
917
+ },
918
+ {
919
+ "epoch": 1.05,
920
+ "eval_bertscore": 0.7334672212600708,
921
+ "eval_loss": 1.739061713218689,
922
+ "eval_rouge1": 0.6552962187824329,
923
+ "eval_rouge2": 0.35210314124279196,
924
+ "eval_rougeL": 0.5272039052368354,
925
+ "eval_rougeLsum": 0.6437473533492806,
926
+ "eval_runtime": 15.5418,
927
+ "eval_samples_per_second": 0.643,
928
+ "eval_steps_per_second": 0.322,
929
+ "step": 9200
930
+ },
931
+ {
932
+ "epoch": 1.07,
933
+ "grad_norm": 0.2909716069698334,
934
+ "learning_rate": 0.00014647791038824168,
935
+ "loss": 1.5276,
936
+ "step": 9400
937
+ },
938
+ {
939
+ "epoch": 1.07,
940
+ "eval_bertscore": 0.7288902997970581,
941
+ "eval_loss": 1.736944556236267,
942
+ "eval_rouge1": 0.6533271685598301,
943
+ "eval_rouge2": 0.35279315321532184,
944
+ "eval_rougeL": 0.5262688234671329,
945
+ "eval_rougeLsum": 0.6424084937151033,
946
+ "eval_runtime": 15.1115,
947
+ "eval_samples_per_second": 0.662,
948
+ "eval_steps_per_second": 0.331,
949
+ "step": 9400
950
+ },
951
+ {
952
+ "epoch": 1.09,
953
+ "grad_norm": 0.3035859763622284,
954
+ "learning_rate": 0.00014533853647420743,
955
+ "loss": 1.5445,
956
+ "step": 9600
957
+ },
958
+ {
959
+ "epoch": 1.09,
960
+ "eval_bertscore": 0.7308284044265747,
961
+ "eval_loss": 1.737762689590454,
962
+ "eval_rouge1": 0.6619725777891359,
963
+ "eval_rouge2": 0.3611963714506864,
964
+ "eval_rougeL": 0.5363802967084452,
965
+ "eval_rougeLsum": 0.6516690557971352,
966
+ "eval_runtime": 14.9932,
967
+ "eval_samples_per_second": 0.667,
968
+ "eval_steps_per_second": 0.333,
969
+ "step": 9600
970
+ },
971
+ {
972
+ "epoch": 1.12,
973
+ "grad_norm": 0.26574915647506714,
974
+ "learning_rate": 0.0001441991625601732,
975
+ "loss": 1.5342,
976
+ "step": 9800
977
+ },
978
+ {
979
+ "epoch": 1.12,
980
+ "eval_bertscore": 0.7328712344169617,
981
+ "eval_loss": 1.7393991947174072,
982
+ "eval_rouge1": 0.6856504003396884,
983
+ "eval_rouge2": 0.3761098841062477,
984
+ "eval_rougeL": 0.555477293163325,
985
+ "eval_rougeLsum": 0.6757574283262289,
986
+ "eval_runtime": 14.8121,
987
+ "eval_samples_per_second": 0.675,
988
+ "eval_steps_per_second": 0.338,
989
+ "step": 9800
990
+ },
991
+ {
992
+ "epoch": 1.14,
993
+ "grad_norm": 0.315468430519104,
994
+ "learning_rate": 0.00014305978864613897,
995
+ "loss": 1.543,
996
+ "step": 10000
997
+ },
998
+ {
999
+ "epoch": 1.14,
1000
+ "eval_bertscore": 0.7349387407302856,
1001
+ "eval_loss": 1.7352710962295532,
1002
+ "eval_rouge1": 0.6749953128982036,
1003
+ "eval_rouge2": 0.3720385250530084,
1004
+ "eval_rougeL": 0.5472261566474382,
1005
+ "eval_rougeLsum": 0.6657643539219252,
1006
+ "eval_runtime": 14.909,
1007
+ "eval_samples_per_second": 0.671,
1008
+ "eval_steps_per_second": 0.335,
1009
+ "step": 10000
1010
+ },
1011
+ {
1012
+ "epoch": 1.16,
1013
+ "grad_norm": 0.29815027117729187,
1014
+ "learning_rate": 0.00014192041473210472,
1015
+ "loss": 1.5547,
1016
+ "step": 10200
1017
+ },
1018
+ {
1019
+ "epoch": 1.16,
1020
+ "eval_bertscore": 0.7359883189201355,
1021
+ "eval_loss": 1.7269136905670166,
1022
+ "eval_rouge1": 0.6561141614088863,
1023
+ "eval_rouge2": 0.3606175666303814,
1024
+ "eval_rougeL": 0.5302270771032793,
1025
+ "eval_rougeLsum": 0.6446912079521883,
1026
+ "eval_runtime": 14.9527,
1027
+ "eval_samples_per_second": 0.669,
1028
+ "eval_steps_per_second": 0.334,
1029
+ "step": 10200
1030
+ },
1031
+ {
1032
+ "epoch": 1.18,
1033
+ "grad_norm": 0.3595702350139618,
1034
+ "learning_rate": 0.00014078104081807047,
1035
+ "loss": 1.5567,
1036
+ "step": 10400
1037
+ },
1038
+ {
1039
+ "epoch": 1.18,
1040
+ "eval_bertscore": 0.7328116297721863,
1041
+ "eval_loss": 1.7341644763946533,
1042
+ "eval_rouge1": 0.6420332714823549,
1043
+ "eval_rouge2": 0.35094864549032,
1044
+ "eval_rougeL": 0.5179556761398367,
1045
+ "eval_rougeLsum": 0.631987397226809,
1046
+ "eval_runtime": 15.1438,
1047
+ "eval_samples_per_second": 0.66,
1048
+ "eval_steps_per_second": 0.33,
1049
+ "step": 10400
1050
+ },
1051
+ {
1052
+ "epoch": 1.21,
1053
+ "grad_norm": 0.2718666195869446,
1054
+ "learning_rate": 0.00013964166690403623,
1055
+ "loss": 1.5408,
1056
+ "step": 10600
1057
+ },
1058
+ {
1059
+ "epoch": 1.21,
1060
+ "eval_bertscore": 0.7337731122970581,
1061
+ "eval_loss": 1.7330901622772217,
1062
+ "eval_rouge1": 0.661681342484687,
1063
+ "eval_rouge2": 0.3626833509973693,
1064
+ "eval_rougeL": 0.5329424447373774,
1065
+ "eval_rougeLsum": 0.6519750177144633,
1066
+ "eval_runtime": 14.8142,
1067
+ "eval_samples_per_second": 0.675,
1068
+ "eval_steps_per_second": 0.338,
1069
+ "step": 10600
1070
+ },
1071
+ {
1072
+ "epoch": 1.23,
1073
+ "grad_norm": 0.29183274507522583,
1074
+ "learning_rate": 0.00013850229299000198,
1075
+ "loss": 1.5422,
1076
+ "step": 10800
1077
+ },
1078
+ {
1079
+ "epoch": 1.23,
1080
+ "eval_bertscore": 0.7331051230430603,
1081
+ "eval_loss": 1.7297636270523071,
1082
+ "eval_rouge1": 0.6655497978238063,
1083
+ "eval_rouge2": 0.3614235788441926,
1084
+ "eval_rougeL": 0.5327210061667442,
1085
+ "eval_rougeLsum": 0.6548836840483913,
1086
+ "eval_runtime": 15.1359,
1087
+ "eval_samples_per_second": 0.661,
1088
+ "eval_steps_per_second": 0.33,
1089
+ "step": 10800
1090
+ },
1091
+ {
1092
+ "epoch": 1.25,
1093
+ "grad_norm": 0.30979740619659424,
1094
+ "learning_rate": 0.00013736291907596776,
1095
+ "loss": 1.5372,
1096
+ "step": 11000
1097
+ },
1098
+ {
1099
+ "epoch": 1.25,
1100
+ "eval_bertscore": 0.7312799692153931,
1101
+ "eval_loss": 1.732444167137146,
1102
+ "eval_rouge1": 0.6568292865033993,
1103
+ "eval_rouge2": 0.35876682221562006,
1104
+ "eval_rougeL": 0.5300878844981931,
1105
+ "eval_rougeLsum": 0.6461751645858989,
1106
+ "eval_runtime": 14.819,
1107
+ "eval_samples_per_second": 0.675,
1108
+ "eval_steps_per_second": 0.337,
1109
+ "step": 11000
1110
+ },
1111
+ {
1112
+ "epoch": 1.28,
1113
+ "grad_norm": 0.31343138217926025,
1114
+ "learning_rate": 0.0001362235451619335,
1115
+ "loss": 1.5301,
1116
+ "step": 11200
1117
+ },
1118
+ {
1119
+ "epoch": 1.28,
1120
+ "eval_bertscore": 0.7317885160446167,
1121
+ "eval_loss": 1.7358499765396118,
1122
+ "eval_rouge1": 0.6548673097943329,
1123
+ "eval_rouge2": 0.3609116081432997,
1124
+ "eval_rougeL": 0.5279887650752133,
1125
+ "eval_rougeLsum": 0.6466232329097188,
1126
+ "eval_runtime": 14.8259,
1127
+ "eval_samples_per_second": 0.674,
1128
+ "eval_steps_per_second": 0.337,
1129
+ "step": 11200
1130
+ },
1131
+ {
1132
+ "epoch": 1.3,
1133
+ "grad_norm": 0.36181533336639404,
1134
+ "learning_rate": 0.0001350841712478993,
1135
+ "loss": 1.5421,
1136
+ "step": 11400
1137
+ },
1138
+ {
1139
+ "epoch": 1.3,
1140
+ "eval_bertscore": 0.7316756248474121,
1141
+ "eval_loss": 1.7282969951629639,
1142
+ "eval_rouge1": 0.6551882964480251,
1143
+ "eval_rouge2": 0.3580708921400697,
1144
+ "eval_rougeL": 0.5255367305995147,
1145
+ "eval_rougeLsum": 0.6449192953008009,
1146
+ "eval_runtime": 14.8816,
1147
+ "eval_samples_per_second": 0.672,
1148
+ "eval_steps_per_second": 0.336,
1149
+ "step": 11400
1150
+ },
1151
+ {
1152
+ "epoch": 1.32,
1153
+ "grad_norm": 0.30600836873054504,
1154
+ "learning_rate": 0.00013394479733386505,
1155
+ "loss": 1.5538,
1156
+ "step": 11600
1157
+ },
1158
+ {
1159
+ "epoch": 1.32,
1160
+ "eval_bertscore": 0.7311854362487793,
1161
+ "eval_loss": 1.7313562631607056,
1162
+ "eval_rouge1": 0.6592751199424156,
1163
+ "eval_rouge2": 0.35802855072854206,
1164
+ "eval_rougeL": 0.5297288176377084,
1165
+ "eval_rougeLsum": 0.6489455314962717,
1166
+ "eval_runtime": 15.0693,
1167
+ "eval_samples_per_second": 0.664,
1168
+ "eval_steps_per_second": 0.332,
1169
+ "step": 11600
1170
+ },
1171
+ {
1172
+ "epoch": 1.34,
1173
+ "grad_norm": 0.29904893040657043,
1174
+ "learning_rate": 0.0001328054234198308,
1175
+ "loss": 1.5328,
1176
+ "step": 11800
1177
+ },
1178
+ {
1179
+ "epoch": 1.34,
1180
+ "eval_bertscore": 0.7312635183334351,
1181
+ "eval_loss": 1.7318429946899414,
1182
+ "eval_rouge1": 0.6577169369077195,
1183
+ "eval_rouge2": 0.3582474830918887,
1184
+ "eval_rougeL": 0.5314990647771975,
1185
+ "eval_rougeLsum": 0.6454785220479866,
1186
+ "eval_runtime": 15.0235,
1187
+ "eval_samples_per_second": 0.666,
1188
+ "eval_steps_per_second": 0.333,
1189
+ "step": 11800
1190
+ },
1191
+ {
1192
+ "epoch": 1.37,
1193
+ "grad_norm": 0.3025416433811188,
1194
+ "learning_rate": 0.00013166604950579658,
1195
+ "loss": 1.5349,
1196
+ "step": 12000
1197
+ },
1198
+ {
1199
+ "epoch": 1.37,
1200
+ "eval_bertscore": 0.7325812578201294,
1201
+ "eval_loss": 1.7309118509292603,
1202
+ "eval_rouge1": 0.6629133074951261,
1203
+ "eval_rouge2": 0.3678158453940578,
1204
+ "eval_rougeL": 0.5380936907276155,
1205
+ "eval_rougeLsum": 0.654883061928214,
1206
+ "eval_runtime": 14.7666,
1207
+ "eval_samples_per_second": 0.677,
1208
+ "eval_steps_per_second": 0.339,
1209
+ "step": 12000
1210
+ },
1211
+ {
1212
+ "epoch": 1.39,
1213
+ "grad_norm": 0.34982389211654663,
1214
+ "learning_rate": 0.00013052667559176233,
1215
+ "loss": 1.5513,
1216
+ "step": 12200
1217
+ },
1218
+ {
1219
+ "epoch": 1.39,
1220
+ "eval_bertscore": 0.7340582609176636,
1221
+ "eval_loss": 1.7363474369049072,
1222
+ "eval_rouge1": 0.6555817937418287,
1223
+ "eval_rouge2": 0.35630500078358396,
1224
+ "eval_rougeL": 0.5272412353478366,
1225
+ "eval_rougeLsum": 0.6445837479327643,
1226
+ "eval_runtime": 14.9664,
1227
+ "eval_samples_per_second": 0.668,
1228
+ "eval_steps_per_second": 0.334,
1229
+ "step": 12200
1230
+ },
1231
+ {
1232
+ "epoch": 1.41,
1233
+ "grad_norm": 0.35809043049812317,
1234
+ "learning_rate": 0.0001293873016777281,
1235
+ "loss": 1.5444,
1236
+ "step": 12400
1237
+ },
1238
+ {
1239
+ "epoch": 1.41,
1240
+ "eval_bertscore": 0.7334069013595581,
1241
+ "eval_loss": 1.7328729629516602,
1242
+ "eval_rouge1": 0.6617971237669364,
1243
+ "eval_rouge2": 0.35951260376512423,
1244
+ "eval_rougeL": 0.5345512305507059,
1245
+ "eval_rougeLsum": 0.648363531132752,
1246
+ "eval_runtime": 15.2146,
1247
+ "eval_samples_per_second": 0.657,
1248
+ "eval_steps_per_second": 0.329,
1249
+ "step": 12400
1250
+ },
1251
+ {
1252
+ "epoch": 1.44,
1253
+ "grad_norm": 0.2954196631908417,
1254
+ "learning_rate": 0.00012824792776369387,
1255
+ "loss": 1.5406,
1256
+ "step": 12600
1257
+ },
1258
+ {
1259
+ "epoch": 1.44,
1260
+ "eval_bertscore": 0.7321678400039673,
1261
+ "eval_loss": 1.7335160970687866,
1262
+ "eval_rouge1": 0.6573625593086756,
1263
+ "eval_rouge2": 0.36210525247389347,
1264
+ "eval_rougeL": 0.5379361120230158,
1265
+ "eval_rougeLsum": 0.6459787883452857,
1266
+ "eval_runtime": 14.8942,
1267
+ "eval_samples_per_second": 0.671,
1268
+ "eval_steps_per_second": 0.336,
1269
+ "step": 12600
1270
+ },
1271
+ {
1272
+ "epoch": 1.46,
1273
+ "grad_norm": 0.32190588116645813,
1274
+ "learning_rate": 0.00012710855384965962,
1275
+ "loss": 1.5491,
1276
+ "step": 12800
1277
+ },
1278
+ {
1279
+ "epoch": 1.46,
1280
+ "eval_bertscore": 0.7346011400222778,
1281
+ "eval_loss": 1.7364966869354248,
1282
+ "eval_rouge1": 0.6481210247390559,
1283
+ "eval_rouge2": 0.3521173896017687,
1284
+ "eval_rougeL": 0.5240500581372636,
1285
+ "eval_rougeLsum": 0.63706442433335,
1286
+ "eval_runtime": 14.923,
1287
+ "eval_samples_per_second": 0.67,
1288
+ "eval_steps_per_second": 0.335,
1289
+ "step": 12800
1290
+ },
1291
+ {
1292
+ "epoch": 1.48,
1293
+ "grad_norm": 0.33323267102241516,
1294
+ "learning_rate": 0.00012596917993562537,
1295
+ "loss": 1.5596,
1296
+ "step": 13000
1297
+ },
1298
+ {
1299
+ "epoch": 1.48,
1300
+ "eval_bertscore": 0.7331587076187134,
1301
+ "eval_loss": 1.7332260608673096,
1302
+ "eval_rouge1": 0.6561257401878793,
1303
+ "eval_rouge2": 0.3548063723792664,
1304
+ "eval_rougeL": 0.527807776001489,
1305
+ "eval_rougeLsum": 0.6451911907984706,
1306
+ "eval_runtime": 15.4703,
1307
+ "eval_samples_per_second": 0.646,
1308
+ "eval_steps_per_second": 0.323,
1309
+ "step": 13000
1310
+ },
1311
+ {
1312
+ "epoch": 1.5,
1313
+ "grad_norm": 0.3564057946205139,
1314
+ "learning_rate": 0.00012482980602159113,
1315
+ "loss": 1.5261,
1316
+ "step": 13200
1317
+ },
1318
+ {
1319
+ "epoch": 1.5,
1320
+ "eval_bertscore": 0.7306063771247864,
1321
+ "eval_loss": 1.7368810176849365,
1322
+ "eval_rouge1": 0.637722723890071,
1323
+ "eval_rouge2": 0.3455358728458236,
1324
+ "eval_rougeL": 0.5136372690435154,
1325
+ "eval_rougeLsum": 0.6273570573595115,
1326
+ "eval_runtime": 15.3533,
1327
+ "eval_samples_per_second": 0.651,
1328
+ "eval_steps_per_second": 0.326,
1329
+ "step": 13200
1330
+ },
1331
+ {
1332
+ "epoch": 1.53,
1333
+ "grad_norm": 0.29219934344291687,
1334
+ "learning_rate": 0.0001236904321075569,
1335
+ "loss": 1.519,
1336
+ "step": 13400
1337
+ },
1338
+ {
1339
+ "epoch": 1.53,
1340
+ "eval_bertscore": 0.7338696122169495,
1341
+ "eval_loss": 1.734724998474121,
1342
+ "eval_rouge1": 0.6442107446420164,
1343
+ "eval_rouge2": 0.3494748457109431,
1344
+ "eval_rougeL": 0.5207483892007314,
1345
+ "eval_rougeLsum": 0.632886404907802,
1346
+ "eval_runtime": 15.3077,
1347
+ "eval_samples_per_second": 0.653,
1348
+ "eval_steps_per_second": 0.327,
1349
+ "step": 13400
1350
+ },
1351
+ {
1352
+ "epoch": 1.55,
1353
+ "grad_norm": 0.34681758284568787,
1354
+ "learning_rate": 0.00012255105819352266,
1355
+ "loss": 1.5419,
1356
+ "step": 13600
1357
+ },
1358
+ {
1359
+ "epoch": 1.55,
1360
+ "eval_bertscore": 0.7350045442581177,
1361
+ "eval_loss": 1.7329858541488647,
1362
+ "eval_rouge1": 0.6606839869796519,
1363
+ "eval_rouge2": 0.362188561160822,
1364
+ "eval_rougeL": 0.5342033818317451,
1365
+ "eval_rougeLsum": 0.6493340000068861,
1366
+ "eval_runtime": 15.44,
1367
+ "eval_samples_per_second": 0.648,
1368
+ "eval_steps_per_second": 0.324,
1369
+ "step": 13600
1370
+ },
1371
+ {
1372
+ "epoch": 1.57,
1373
+ "grad_norm": 0.3043666481971741,
1374
+ "learning_rate": 0.00012141168427948844,
1375
+ "loss": 1.5402,
1376
+ "step": 13800
1377
+ },
1378
+ {
1379
+ "epoch": 1.57,
1380
+ "eval_bertscore": 0.7363221645355225,
1381
+ "eval_loss": 1.7308530807495117,
1382
+ "eval_rouge1": 0.6638252384356028,
1383
+ "eval_rouge2": 0.3643237697892826,
1384
+ "eval_rougeL": 0.5403775887381331,
1385
+ "eval_rougeLsum": 0.6537260000827279,
1386
+ "eval_runtime": 14.7668,
1387
+ "eval_samples_per_second": 0.677,
1388
+ "eval_steps_per_second": 0.339,
1389
+ "step": 13800
1390
+ },
1391
+ {
1392
+ "epoch": 1.59,
1393
+ "grad_norm": 0.4073585867881775,
1394
+ "learning_rate": 0.00012027231036545419,
1395
+ "loss": 1.5256,
1396
+ "step": 14000
1397
+ },
1398
+ {
1399
+ "epoch": 1.59,
1400
+ "eval_bertscore": 0.7310279607772827,
1401
+ "eval_loss": 1.7326784133911133,
1402
+ "eval_rouge1": 0.6609594314120198,
1403
+ "eval_rouge2": 0.3601530714440473,
1404
+ "eval_rougeL": 0.5344452687135626,
1405
+ "eval_rougeLsum": 0.6480936554342305,
1406
+ "eval_runtime": 14.8565,
1407
+ "eval_samples_per_second": 0.673,
1408
+ "eval_steps_per_second": 0.337,
1409
+ "step": 14000
1410
+ },
1411
+ {
1412
+ "epoch": 1.62,
1413
+ "grad_norm": 0.3211813271045685,
1414
+ "learning_rate": 0.00011913293645141995,
1415
+ "loss": 1.5366,
1416
+ "step": 14200
1417
+ },
1418
+ {
1419
+ "epoch": 1.62,
1420
+ "eval_bertscore": 0.7356667518615723,
1421
+ "eval_loss": 1.7280094623565674,
1422
+ "eval_rouge1": 0.6519353227375031,
1423
+ "eval_rouge2": 0.3587025716186173,
1424
+ "eval_rougeL": 0.5306356200586075,
1425
+ "eval_rougeLsum": 0.6408870347994059,
1426
+ "eval_runtime": 14.9264,
1427
+ "eval_samples_per_second": 0.67,
1428
+ "eval_steps_per_second": 0.335,
1429
+ "step": 14200
1430
+ },
1431
+ {
1432
+ "epoch": 1.64,
1433
+ "grad_norm": 0.32776832580566406,
1434
+ "learning_rate": 0.00011799356253738571,
1435
+ "loss": 1.5504,
1436
+ "step": 14400
1437
+ },
1438
+ {
1439
+ "epoch": 1.64,
1440
+ "eval_bertscore": 0.7331353425979614,
1441
+ "eval_loss": 1.7308950424194336,
1442
+ "eval_rouge1": 0.6627702292814652,
1443
+ "eval_rouge2": 0.36117793957379707,
1444
+ "eval_rougeL": 0.5369305446079228,
1445
+ "eval_rougeLsum": 0.6516924083980089,
1446
+ "eval_runtime": 16.0138,
1447
+ "eval_samples_per_second": 0.624,
1448
+ "eval_steps_per_second": 0.312,
1449
+ "step": 14400
1450
+ },
1451
+ {
1452
+ "epoch": 1.66,
1453
+ "grad_norm": 0.3209726810455322,
1454
+ "learning_rate": 0.00011685418862335147,
1455
+ "loss": 1.5473,
1456
+ "step": 14600
1457
+ },
1458
+ {
1459
+ "epoch": 1.66,
1460
+ "eval_bertscore": 0.732498824596405,
1461
+ "eval_loss": 1.7328402996063232,
1462
+ "eval_rouge1": 0.6482679740803596,
1463
+ "eval_rouge2": 0.3538726087405498,
1464
+ "eval_rougeL": 0.5267677183598017,
1465
+ "eval_rougeLsum": 0.6366529460029322,
1466
+ "eval_runtime": 15.0195,
1467
+ "eval_samples_per_second": 0.666,
1468
+ "eval_steps_per_second": 0.333,
1469
+ "step": 14600
1470
+ },
1471
+ {
1472
+ "epoch": 1.69,
1473
+ "grad_norm": 0.3174591064453125,
1474
+ "learning_rate": 0.00011571481470931725,
1475
+ "loss": 1.5568,
1476
+ "step": 14800
1477
+ },
1478
+ {
1479
+ "epoch": 1.69,
1480
+ "eval_bertscore": 0.7335298657417297,
1481
+ "eval_loss": 1.7310253381729126,
1482
+ "eval_rouge1": 0.6560468577439627,
1483
+ "eval_rouge2": 0.36039371229175,
1484
+ "eval_rougeL": 0.5318708569729291,
1485
+ "eval_rougeLsum": 0.6444857558837042,
1486
+ "eval_runtime": 14.9774,
1487
+ "eval_samples_per_second": 0.668,
1488
+ "eval_steps_per_second": 0.334,
1489
+ "step": 14800
1490
+ },
1491
+ {
1492
+ "epoch": 1.71,
1493
+ "grad_norm": 0.2936408817768097,
1494
+ "learning_rate": 0.000114575440795283,
1495
+ "loss": 1.5345,
1496
+ "step": 15000
1497
+ },
1498
+ {
1499
+ "epoch": 1.71,
1500
+ "eval_bertscore": 0.7322725057601929,
1501
+ "eval_loss": 1.7270629405975342,
1502
+ "eval_rouge1": 0.6387060930656672,
1503
+ "eval_rouge2": 0.3480508127989137,
1504
+ "eval_rougeL": 0.5148670834213287,
1505
+ "eval_rougeLsum": 0.6273654952601909,
1506
+ "eval_runtime": 15.6687,
1507
+ "eval_samples_per_second": 0.638,
1508
+ "eval_steps_per_second": 0.319,
1509
+ "step": 15000
1510
+ },
1511
+ {
1512
+ "epoch": 1.73,
1513
+ "grad_norm": 0.32960689067840576,
1514
+ "learning_rate": 0.00011343606688124875,
1515
+ "loss": 1.5362,
1516
+ "step": 15200
1517
+ },
1518
+ {
1519
+ "epoch": 1.73,
1520
+ "eval_bertscore": 0.7337037920951843,
1521
+ "eval_loss": 1.7287395000457764,
1522
+ "eval_rouge1": 0.6476816970229771,
1523
+ "eval_rouge2": 0.3532248216683249,
1524
+ "eval_rougeL": 0.5253136618838716,
1525
+ "eval_rougeLsum": 0.6347493764394183,
1526
+ "eval_runtime": 15.0045,
1527
+ "eval_samples_per_second": 0.666,
1528
+ "eval_steps_per_second": 0.333,
1529
+ "step": 15200
1530
+ },
1531
+ {
1532
+ "epoch": 1.75,
1533
+ "grad_norm": 0.33265602588653564,
1534
+ "learning_rate": 0.00011229669296721452,
1535
+ "loss": 1.5215,
1536
+ "step": 15400
1537
+ },
1538
+ {
1539
+ "epoch": 1.75,
1540
+ "eval_bertscore": 0.7330806851387024,
1541
+ "eval_loss": 1.7265052795410156,
1542
+ "eval_rouge1": 0.6529393512177359,
1543
+ "eval_rouge2": 0.36182153145062224,
1544
+ "eval_rougeL": 0.5317061134915853,
1545
+ "eval_rougeLsum": 0.6413066299251913,
1546
+ "eval_runtime": 15.0256,
1547
+ "eval_samples_per_second": 0.666,
1548
+ "eval_steps_per_second": 0.333,
1549
+ "step": 15400
1550
+ },
1551
+ {
1552
+ "epoch": 1.78,
1553
+ "grad_norm": 0.3436201512813568,
1554
+ "learning_rate": 0.00011115731905318027,
1555
+ "loss": 1.539,
1556
+ "step": 15600
1557
+ },
1558
+ {
1559
+ "epoch": 1.78,
1560
+ "eval_bertscore": 0.7335551977157593,
1561
+ "eval_loss": 1.7254730463027954,
1562
+ "eval_rouge1": 0.6388518781767971,
1563
+ "eval_rouge2": 0.3501853846588857,
1564
+ "eval_rougeL": 0.5196828245794569,
1565
+ "eval_rougeLsum": 0.629333993884722,
1566
+ "eval_runtime": 15.2595,
1567
+ "eval_samples_per_second": 0.655,
1568
+ "eval_steps_per_second": 0.328,
1569
+ "step": 15600
1570
+ },
1571
+ {
1572
+ "epoch": 1.8,
1573
+ "grad_norm": 0.3428190350532532,
1574
+ "learning_rate": 0.00011001794513914605,
1575
+ "loss": 1.5273,
1576
+ "step": 15800
1577
+ },
1578
+ {
1579
+ "epoch": 1.8,
1580
+ "eval_bertscore": 0.7331770658493042,
1581
+ "eval_loss": 1.7286018133163452,
1582
+ "eval_rouge1": 0.6581941047310954,
1583
+ "eval_rouge2": 0.36277983926897583,
1584
+ "eval_rougeL": 0.5336464680120501,
1585
+ "eval_rougeLsum": 0.6489239720278894,
1586
+ "eval_runtime": 14.8252,
1587
+ "eval_samples_per_second": 0.675,
1588
+ "eval_steps_per_second": 0.337,
1589
+ "step": 15800
1590
+ },
1591
+ {
1592
+ "epoch": 1.82,
1593
+ "grad_norm": 0.363164484500885,
1594
+ "learning_rate": 0.0001088785712251118,
1595
+ "loss": 1.5445,
1596
+ "step": 16000
1597
+ },
1598
+ {
1599
+ "epoch": 1.82,
1600
+ "eval_bertscore": 0.7377282977104187,
1601
+ "eval_loss": 1.7363064289093018,
1602
+ "eval_rouge1": 0.6547011011872876,
1603
+ "eval_rouge2": 0.3553220826957326,
1604
+ "eval_rougeL": 0.5256073814411315,
1605
+ "eval_rougeLsum": 0.6420095316923398,
1606
+ "eval_runtime": 14.8599,
1607
+ "eval_samples_per_second": 0.673,
1608
+ "eval_steps_per_second": 0.336,
1609
+ "step": 16000
1610
+ },
1611
+ {
1612
+ "epoch": 1.85,
1613
+ "grad_norm": 0.3098333775997162,
1614
+ "learning_rate": 0.00010773919731107757,
1615
+ "loss": 1.5319,
1616
+ "step": 16200
1617
+ },
1618
+ {
1619
+ "epoch": 1.85,
1620
+ "eval_bertscore": 0.7324053645133972,
1621
+ "eval_loss": 1.7284066677093506,
1622
+ "eval_rouge1": 0.6477379941950916,
1623
+ "eval_rouge2": 0.3535918140554809,
1624
+ "eval_rougeL": 0.5226838544730126,
1625
+ "eval_rougeLsum": 0.6373271915355557,
1626
+ "eval_runtime": 14.9318,
1627
+ "eval_samples_per_second": 0.67,
1628
+ "eval_steps_per_second": 0.335,
1629
+ "step": 16200
1630
+ },
1631
+ {
1632
+ "epoch": 1.87,
1633
+ "grad_norm": 0.3637208938598633,
1634
+ "learning_rate": 0.00010659982339704332,
1635
+ "loss": 1.5442,
1636
+ "step": 16400
1637
+ },
1638
+ {
1639
+ "epoch": 1.87,
1640
+ "eval_bertscore": 0.7347462773323059,
1641
+ "eval_loss": 1.7252963781356812,
1642
+ "eval_rouge1": 0.6494449840449819,
1643
+ "eval_rouge2": 0.3586550050575282,
1644
+ "eval_rougeL": 0.5275675395159809,
1645
+ "eval_rougeLsum": 0.6396738714026391,
1646
+ "eval_runtime": 15.2218,
1647
+ "eval_samples_per_second": 0.657,
1648
+ "eval_steps_per_second": 0.328,
1649
+ "step": 16400
1650
+ },
1651
+ {
1652
+ "epoch": 1.89,
1653
+ "grad_norm": 0.35197457671165466,
1654
+ "learning_rate": 0.00010546044948300908,
1655
+ "loss": 1.5131,
1656
+ "step": 16600
1657
+ },
1658
+ {
1659
+ "epoch": 1.89,
1660
+ "eval_bertscore": 0.7329785227775574,
1661
+ "eval_loss": 1.7285687923431396,
1662
+ "eval_rouge1": 0.6582047811143328,
1663
+ "eval_rouge2": 0.3637700686094697,
1664
+ "eval_rougeL": 0.5355021948480279,
1665
+ "eval_rougeLsum": 0.6483245595148677,
1666
+ "eval_runtime": 14.8772,
1667
+ "eval_samples_per_second": 0.672,
1668
+ "eval_steps_per_second": 0.336,
1669
+ "step": 16600
1670
+ },
1671
+ {
1672
+ "epoch": 1.91,
1673
+ "grad_norm": 0.3406757116317749,
1674
+ "learning_rate": 0.00010432107556897486,
1675
+ "loss": 1.5394,
1676
+ "step": 16800
1677
+ },
1678
+ {
1679
+ "epoch": 1.91,
1680
+ "eval_bertscore": 0.7345961332321167,
1681
+ "eval_loss": 1.7324028015136719,
1682
+ "eval_rouge1": 0.6408293615351552,
1683
+ "eval_rouge2": 0.3520120690778129,
1684
+ "eval_rougeL": 0.5145218014745592,
1685
+ "eval_rougeLsum": 0.6297802607384266,
1686
+ "eval_runtime": 15.1044,
1687
+ "eval_samples_per_second": 0.662,
1688
+ "eval_steps_per_second": 0.331,
1689
+ "step": 16800
1690
+ },
1691
+ {
1692
+ "epoch": 1.94,
1693
+ "grad_norm": 0.3417683243751526,
1694
+ "learning_rate": 0.00010318170165494061,
1695
+ "loss": 1.526,
1696
+ "step": 17000
1697
+ },
1698
+ {
1699
+ "epoch": 1.94,
1700
+ "eval_bertscore": 0.735752522945404,
1701
+ "eval_loss": 1.7288110256195068,
1702
+ "eval_rouge1": 0.641158513352794,
1703
+ "eval_rouge2": 0.3544166440855814,
1704
+ "eval_rougeL": 0.5215201980495414,
1705
+ "eval_rougeLsum": 0.630550065494593,
1706
+ "eval_runtime": 15.0797,
1707
+ "eval_samples_per_second": 0.663,
1708
+ "eval_steps_per_second": 0.332,
1709
+ "step": 17000
1710
+ },
1711
+ {
1712
+ "epoch": 1.96,
1713
+ "grad_norm": 0.3256611227989197,
1714
+ "learning_rate": 0.00010204232774090639,
1715
+ "loss": 1.5484,
1716
+ "step": 17200
1717
+ },
1718
+ {
1719
+ "epoch": 1.96,
1720
+ "eval_bertscore": 0.7356327772140503,
1721
+ "eval_loss": 1.7305186986923218,
1722
+ "eval_rouge1": 0.6400269226515611,
1723
+ "eval_rouge2": 0.3502884634173268,
1724
+ "eval_rougeL": 0.517312321281175,
1725
+ "eval_rougeLsum": 0.6284556997614409,
1726
+ "eval_runtime": 15.4097,
1727
+ "eval_samples_per_second": 0.649,
1728
+ "eval_steps_per_second": 0.324,
1729
+ "step": 17200
1730
+ },
1731
+ {
1732
+ "epoch": 1.98,
1733
+ "grad_norm": 0.4035187363624573,
1734
+ "learning_rate": 0.00010090295382687213,
1735
+ "loss": 1.5261,
1736
+ "step": 17400
1737
+ },
1738
+ {
1739
+ "epoch": 1.98,
1740
+ "eval_bertscore": 0.7339992523193359,
1741
+ "eval_loss": 1.7282793521881104,
1742
+ "eval_rouge1": 0.6335770390416183,
1743
+ "eval_rouge2": 0.34592404578075897,
1744
+ "eval_rougeL": 0.5109045259792113,
1745
+ "eval_rougeLsum": 0.6218413683710426,
1746
+ "eval_runtime": 15.1959,
1747
+ "eval_samples_per_second": 0.658,
1748
+ "eval_steps_per_second": 0.329,
1749
+ "step": 17400
1750
+ },
1751
+ {
1752
+ "epoch": 2.0,
1753
+ "grad_norm": 0.34987062215805054,
1754
+ "learning_rate": 9.97635799128379e-05,
1755
+ "loss": 1.5199,
1756
+ "step": 17600
1757
+ },
1758
+ {
1759
+ "epoch": 2.0,
1760
+ "eval_bertscore": 0.7326329946517944,
1761
+ "eval_loss": 1.7544715404510498,
1762
+ "eval_rouge1": 0.6451558045750205,
1763
+ "eval_rouge2": 0.35565806935653943,
1764
+ "eval_rougeL": 0.5217034865840529,
1765
+ "eval_rougeLsum": 0.6329869715356753,
1766
+ "eval_runtime": 15.0351,
1767
+ "eval_samples_per_second": 0.665,
1768
+ "eval_steps_per_second": 0.333,
1769
+ "step": 17600
1770
+ },
1771
+ {
1772
+ "epoch": 2.03,
1773
+ "grad_norm": 0.37184038758277893,
1774
+ "learning_rate": 9.862420599880366e-05,
1775
+ "loss": 1.41,
1776
+ "step": 17800
1777
+ },
1778
+ {
1779
+ "epoch": 2.03,
1780
+ "eval_bertscore": 0.7315141558647156,
1781
+ "eval_loss": 1.7585878372192383,
1782
+ "eval_rouge1": 0.6469319193583706,
1783
+ "eval_rouge2": 0.3514447211469598,
1784
+ "eval_rougeL": 0.524755857688278,
1785
+ "eval_rougeLsum": 0.6350164781858667,
1786
+ "eval_runtime": 14.9583,
1787
+ "eval_samples_per_second": 0.669,
1788
+ "eval_steps_per_second": 0.334,
1789
+ "step": 17800
1790
+ },
1791
+ {
1792
+ "epoch": 2.05,
1793
+ "grad_norm": 0.3812776803970337,
1794
+ "learning_rate": 9.748483208476943e-05,
1795
+ "loss": 1.4132,
1796
+ "step": 18000
1797
+ },
1798
+ {
1799
+ "epoch": 2.05,
1800
+ "eval_bertscore": 0.7335561513900757,
1801
+ "eval_loss": 1.764611840248108,
1802
+ "eval_rouge1": 0.6381916780473581,
1803
+ "eval_rouge2": 0.3482510604092539,
1804
+ "eval_rougeL": 0.5162105225823392,
1805
+ "eval_rougeLsum": 0.627150245441782,
1806
+ "eval_runtime": 15.8515,
1807
+ "eval_samples_per_second": 0.631,
1808
+ "eval_steps_per_second": 0.315,
1809
+ "step": 18000
1810
+ },
1811
+ {
1812
+ "epoch": 2.07,
1813
+ "grad_norm": 0.45525220036506653,
1814
+ "learning_rate": 9.634545817073518e-05,
1815
+ "loss": 1.4,
1816
+ "step": 18200
1817
+ },
1818
+ {
1819
+ "epoch": 2.07,
1820
+ "eval_bertscore": 0.73627769947052,
1821
+ "eval_loss": 1.7585163116455078,
1822
+ "eval_rouge1": 0.6670097658027134,
1823
+ "eval_rouge2": 0.3658295359911405,
1824
+ "eval_rougeL": 0.5429667657900548,
1825
+ "eval_rougeLsum": 0.6543501745791419,
1826
+ "eval_runtime": 15.0301,
1827
+ "eval_samples_per_second": 0.665,
1828
+ "eval_steps_per_second": 0.333,
1829
+ "step": 18200
1830
+ },
1831
+ {
1832
+ "epoch": 2.1,
1833
+ "grad_norm": 0.37322184443473816,
1834
+ "learning_rate": 9.520608425670095e-05,
1835
+ "loss": 1.4293,
1836
+ "step": 18400
1837
+ },
1838
+ {
1839
+ "epoch": 2.1,
1840
+ "eval_bertscore": 0.730435848236084,
1841
+ "eval_loss": 1.764052391052246,
1842
+ "eval_rouge1": 0.6640215078213034,
1843
+ "eval_rouge2": 0.3625932287322054,
1844
+ "eval_rougeL": 0.5379978391335138,
1845
+ "eval_rougeLsum": 0.6542054656293199,
1846
+ "eval_runtime": 15.0762,
1847
+ "eval_samples_per_second": 0.663,
1848
+ "eval_steps_per_second": 0.332,
1849
+ "step": 18400
1850
+ },
1851
+ {
1852
+ "epoch": 2.12,
1853
+ "grad_norm": 0.4260891079902649,
1854
+ "learning_rate": 9.40667103426667e-05,
1855
+ "loss": 1.4077,
1856
+ "step": 18600
1857
+ },
1858
+ {
1859
+ "epoch": 2.12,
1860
+ "eval_bertscore": 0.7309869527816772,
1861
+ "eval_loss": 1.762108564376831,
1862
+ "eval_rouge1": 0.6571171081737958,
1863
+ "eval_rouge2": 0.35780421333141865,
1864
+ "eval_rougeL": 0.5320129270967632,
1865
+ "eval_rougeLsum": 0.64587787409523,
1866
+ "eval_runtime": 14.9004,
1867
+ "eval_samples_per_second": 0.671,
1868
+ "eval_steps_per_second": 0.336,
1869
+ "step": 18600
1870
+ },
1871
+ {
1872
+ "epoch": 2.14,
1873
+ "grad_norm": 0.39479926228523254,
1874
+ "learning_rate": 9.292733642863247e-05,
1875
+ "loss": 1.4165,
1876
+ "step": 18800
1877
+ },
1878
+ {
1879
+ "epoch": 2.14,
1880
+ "eval_bertscore": 0.7324444651603699,
1881
+ "eval_loss": 1.7607113122940063,
1882
+ "eval_rouge1": 0.6628398862884018,
1883
+ "eval_rouge2": 0.3627259806721216,
1884
+ "eval_rougeL": 0.5366106483832656,
1885
+ "eval_rougeLsum": 0.6528364858807157,
1886
+ "eval_runtime": 15.5766,
1887
+ "eval_samples_per_second": 0.642,
1888
+ "eval_steps_per_second": 0.321,
1889
+ "step": 18800
1890
+ },
1891
+ {
1892
+ "epoch": 2.16,
1893
+ "grad_norm": 0.39267703890800476,
1894
+ "learning_rate": 9.178796251459824e-05,
1895
+ "loss": 1.4123,
1896
+ "step": 19000
1897
+ },
1898
+ {
1899
+ "epoch": 2.16,
1900
+ "eval_bertscore": 0.7298994064331055,
1901
+ "eval_loss": 1.7668545246124268,
1902
+ "eval_rouge1": 0.6490850022857569,
1903
+ "eval_rouge2": 0.3532323419511264,
1904
+ "eval_rougeL": 0.5212823000193295,
1905
+ "eval_rougeLsum": 0.636442724466695,
1906
+ "eval_runtime": 14.9094,
1907
+ "eval_samples_per_second": 0.671,
1908
+ "eval_steps_per_second": 0.335,
1909
+ "step": 19000
1910
+ },
1911
+ {
1912
+ "epoch": 2.19,
1913
+ "grad_norm": 0.38221287727355957,
1914
+ "learning_rate": 9.0648588600564e-05,
1915
+ "loss": 1.401,
1916
+ "step": 19200
1917
+ },
1918
+ {
1919
+ "epoch": 2.19,
1920
+ "eval_bertscore": 0.7316875457763672,
1921
+ "eval_loss": 1.764147400856018,
1922
+ "eval_rouge1": 0.6490326710625849,
1923
+ "eval_rouge2": 0.3510351037900723,
1924
+ "eval_rougeL": 0.5239165028795836,
1925
+ "eval_rougeLsum": 0.6373687316421427,
1926
+ "eval_runtime": 15.1192,
1927
+ "eval_samples_per_second": 0.661,
1928
+ "eval_steps_per_second": 0.331,
1929
+ "step": 19200
1930
+ }
1931
+ ],
1932
+ "logging_steps": 200,
1933
+ "max_steps": 35112,
1934
+ "num_input_tokens_seen": 0,
1935
+ "num_train_epochs": 4,
1936
+ "save_steps": 800,
1937
+ "total_flos": 1.9452726542216356e+18,
1938
+ "train_batch_size": 2,
1939
+ "trial_name": null,
1940
+ "trial_params": null
1941
+ }
checkpoint-19200/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d576743d4294cfbcae212243377437f73cabbcded2df9da7f73e6e39ecb38f56
3
+ size 5048
checkpoint-20000/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: peft
3
+ base_model: unsloth/gemma-2b-bnb-4bit
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.10.0
checkpoint-20000/adapter_config.json ADDED
@@ -0,0 +1,34 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "unsloth/gemma-2b-bnb-4bit",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 32,
14
+ "lora_dropout": 0,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 64,
20
+ "rank_pattern": {},
21
+ "revision": "unsloth",
22
+ "target_modules": [
23
+ "v_proj",
24
+ "up_proj",
25
+ "gate_proj",
26
+ "o_proj",
27
+ "k_proj",
28
+ "down_proj",
29
+ "q_proj"
30
+ ],
31
+ "task_type": "CAUSAL_LM",
32
+ "use_dora": false,
33
+ "use_rslora": false
34
+ }
checkpoint-20000/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:ba64a48660d96e6ae210c02e7b193ff3ddad9dba223c1a63500a488145c438cb
3
+ size 313820248
checkpoint-20000/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:0fba149b3295ba204666aba65c69a1092c2683c7409ae96a94ad417bde27841b
3
+ size 14244
checkpoint-20000/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:de935c76c515679cf99a388f4ac63df38c3b321d9fb6d4b28cb9bf7338ecb1af
3
+ size 1064
checkpoint-20000/special_tokens_map.json ADDED
@@ -0,0 +1,34 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "additional_special_tokens": [
3
+ "<start_of_turn>",
4
+ "<end_of_turn>"
5
+ ],
6
+ "bos_token": {
7
+ "content": "<bos>",
8
+ "lstrip": false,
9
+ "normalized": false,
10
+ "rstrip": false,
11
+ "single_word": false
12
+ },
13
+ "eos_token": {
14
+ "content": "<eos>",
15
+ "lstrip": false,
16
+ "normalized": false,
17
+ "rstrip": false,
18
+ "single_word": false
19
+ },
20
+ "pad_token": {
21
+ "content": "<pad>",
22
+ "lstrip": false,
23
+ "normalized": false,
24
+ "rstrip": false,
25
+ "single_word": false
26
+ },
27
+ "unk_token": {
28
+ "content": "<unk>",
29
+ "lstrip": false,
30
+ "normalized": false,
31
+ "rstrip": false,
32
+ "single_word": false
33
+ }
34
+ }
checkpoint-20000/tokenizer.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:05e97791a5e007260de1db7e1692e53150e08cea481e2bf25435553380c147ee
3
+ size 17477929
checkpoint-20000/tokenizer.model ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:61a7b147390c64585d6c3543dd6fc636906c9af3865a5548f27f31aee1d4c8e2
3
+ size 4241003
checkpoint-20000/tokenizer_config.json ADDED
@@ -0,0 +1,71 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_bos_token": true,
3
+ "add_eos_token": false,
4
+ "added_tokens_decoder": {
5
+ "0": {
6
+ "content": "<pad>",
7
+ "lstrip": false,
8
+ "normalized": false,
9
+ "rstrip": false,
10
+ "single_word": false,
11
+ "special": true
12
+ },
13
+ "1": {
14
+ "content": "<eos>",
15
+ "lstrip": false,
16
+ "normalized": false,
17
+ "rstrip": false,
18
+ "single_word": false,
19
+ "special": true
20
+ },
21
+ "2": {
22
+ "content": "<bos>",
23
+ "lstrip": false,
24
+ "normalized": false,
25
+ "rstrip": false,
26
+ "single_word": false,
27
+ "special": true
28
+ },
29
+ "3": {
30
+ "content": "<unk>",
31
+ "lstrip": false,
32
+ "normalized": false,
33
+ "rstrip": false,
34
+ "single_word": false,
35
+ "special": true
36
+ },
37
+ "106": {
38
+ "content": "<start_of_turn>",
39
+ "lstrip": false,
40
+ "normalized": false,
41
+ "rstrip": false,
42
+ "single_word": false,
43
+ "special": true
44
+ },
45
+ "107": {
46
+ "content": "<end_of_turn>",
47
+ "lstrip": false,
48
+ "normalized": false,
49
+ "rstrip": false,
50
+ "single_word": false,
51
+ "special": true
52
+ }
53
+ },
54
+ "additional_special_tokens": [
55
+ "<start_of_turn>",
56
+ "<end_of_turn>"
57
+ ],
58
+ "bos_token": "<bos>",
59
+ "chat_template": "{{ bos_token }}{% if messages[0]['role'] == 'system' %}{{ raise_exception('System role not supported') }}{% endif %}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if (message['role'] == 'assistant') %}{% set role = 'model' %}{% else %}{% set role = message['role'] %}{% endif %}{{ '<start_of_turn>' + role + '\n' + message['content'] | trim + '<end_of_turn>\n' }}{% endfor %}{% if add_generation_prompt %}{{'<start_of_turn>model\n'}}{% endif %}",
60
+ "clean_up_tokenization_spaces": false,
61
+ "eos_token": "<eos>",
62
+ "legacy": null,
63
+ "model_max_length": 8192,
64
+ "pad_token": "<pad>",
65
+ "padding_side": "right",
66
+ "sp_model_kwargs": {},
67
+ "spaces_between_special_tokens": false,
68
+ "tokenizer_class": "GemmaTokenizer",
69
+ "unk_token": "<unk>",
70
+ "use_default_system_prompt": false
71
+ }
checkpoint-20000/trainer_state.json ADDED
@@ -0,0 +1,2021 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": null,
3
+ "best_model_checkpoint": null,
4
+ "epoch": 2.2782935581249646,
5
+ "eval_steps": 200,
6
+ "global_step": 20000,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.02,
13
+ "grad_norm": 0.1643640249967575,
14
+ "learning_rate": 0.0001988891104338166,
15
+ "loss": 1.7673,
16
+ "step": 200
17
+ },
18
+ {
19
+ "epoch": 0.02,
20
+ "eval_bertscore": 0.7312520742416382,
21
+ "eval_loss": 1.7944419384002686,
22
+ "eval_rouge1": 0.645726048132668,
23
+ "eval_rouge2": 0.342840307585653,
24
+ "eval_rougeL": 0.5174784271125388,
25
+ "eval_rougeLsum": 0.6359911842715976,
26
+ "eval_runtime": 67.7968,
27
+ "eval_samples_per_second": 0.147,
28
+ "eval_steps_per_second": 0.074,
29
+ "step": 200
30
+ },
31
+ {
32
+ "epoch": 0.05,
33
+ "grad_norm": 0.17238478362560272,
34
+ "learning_rate": 0.00019774973651978238,
35
+ "loss": 1.6985,
36
+ "step": 400
37
+ },
38
+ {
39
+ "epoch": 0.05,
40
+ "eval_bertscore": 0.733666718006134,
41
+ "eval_loss": 1.7791178226470947,
42
+ "eval_rouge1": 0.6540909153028596,
43
+ "eval_rouge2": 0.3548819059818129,
44
+ "eval_rougeL": 0.527257232694246,
45
+ "eval_rougeLsum": 0.6442799950994005,
46
+ "eval_runtime": 15.1267,
47
+ "eval_samples_per_second": 0.661,
48
+ "eval_steps_per_second": 0.331,
49
+ "step": 400
50
+ },
51
+ {
52
+ "epoch": 0.07,
53
+ "grad_norm": 0.19368696212768555,
54
+ "learning_rate": 0.00019661036260574814,
55
+ "loss": 1.6962,
56
+ "step": 600
57
+ },
58
+ {
59
+ "epoch": 0.07,
60
+ "eval_bertscore": 0.7339462041854858,
61
+ "eval_loss": 1.7609882354736328,
62
+ "eval_rouge1": 0.6384337329686338,
63
+ "eval_rouge2": 0.3415514270662107,
64
+ "eval_rougeL": 0.51206080148464,
65
+ "eval_rougeLsum": 0.6261968614666548,
66
+ "eval_runtime": 15.2068,
67
+ "eval_samples_per_second": 0.658,
68
+ "eval_steps_per_second": 0.329,
69
+ "step": 600
70
+ },
71
+ {
72
+ "epoch": 0.09,
73
+ "grad_norm": 0.18629203736782074,
74
+ "learning_rate": 0.00019547098869171392,
75
+ "loss": 1.6825,
76
+ "step": 800
77
+ },
78
+ {
79
+ "epoch": 0.09,
80
+ "eval_bertscore": 0.7363594174385071,
81
+ "eval_loss": 1.7610784769058228,
82
+ "eval_rouge1": 0.6461624591922237,
83
+ "eval_rouge2": 0.3477371388439609,
84
+ "eval_rougeL": 0.5187429174752844,
85
+ "eval_rougeLsum": 0.6361089823008282,
86
+ "eval_runtime": 15.173,
87
+ "eval_samples_per_second": 0.659,
88
+ "eval_steps_per_second": 0.33,
89
+ "step": 800
90
+ },
91
+ {
92
+ "epoch": 0.11,
93
+ "grad_norm": 0.1799013316631317,
94
+ "learning_rate": 0.00019433161477767967,
95
+ "loss": 1.6848,
96
+ "step": 1000
97
+ },
98
+ {
99
+ "epoch": 0.11,
100
+ "eval_bertscore": 0.7334067225456238,
101
+ "eval_loss": 1.7576347589492798,
102
+ "eval_rouge1": 0.6345119236349537,
103
+ "eval_rouge2": 0.3422519149071803,
104
+ "eval_rougeL": 0.5111983101326238,
105
+ "eval_rougeLsum": 0.6244653120436832,
106
+ "eval_runtime": 15.2847,
107
+ "eval_samples_per_second": 0.654,
108
+ "eval_steps_per_second": 0.327,
109
+ "step": 1000
110
+ },
111
+ {
112
+ "epoch": 0.14,
113
+ "grad_norm": 0.22036150097846985,
114
+ "learning_rate": 0.00019319224086364545,
115
+ "loss": 1.6714,
116
+ "step": 1200
117
+ },
118
+ {
119
+ "epoch": 0.14,
120
+ "eval_bertscore": 0.7323788404464722,
121
+ "eval_loss": 1.7521806955337524,
122
+ "eval_rouge1": 0.6452540184557478,
123
+ "eval_rouge2": 0.3465145726476423,
124
+ "eval_rougeL": 0.516711757588783,
125
+ "eval_rougeLsum": 0.6341049885677059,
126
+ "eval_runtime": 15.1247,
127
+ "eval_samples_per_second": 0.661,
128
+ "eval_steps_per_second": 0.331,
129
+ "step": 1200
130
+ },
131
+ {
132
+ "epoch": 0.16,
133
+ "grad_norm": 0.21381086111068726,
134
+ "learning_rate": 0.0001920528669496112,
135
+ "loss": 1.6669,
136
+ "step": 1400
137
+ },
138
+ {
139
+ "epoch": 0.16,
140
+ "eval_bertscore": 0.7313202619552612,
141
+ "eval_loss": 1.7520482540130615,
142
+ "eval_rouge1": 0.6397526546254797,
143
+ "eval_rouge2": 0.3452671288110514,
144
+ "eval_rougeL": 0.5176580626678706,
145
+ "eval_rougeLsum": 0.6296746647539768,
146
+ "eval_runtime": 15.183,
147
+ "eval_samples_per_second": 0.659,
148
+ "eval_steps_per_second": 0.329,
149
+ "step": 1400
150
+ },
151
+ {
152
+ "epoch": 0.18,
153
+ "grad_norm": 0.20332874357700348,
154
+ "learning_rate": 0.00019091349303557696,
155
+ "loss": 1.671,
156
+ "step": 1600
157
+ },
158
+ {
159
+ "epoch": 0.18,
160
+ "eval_bertscore": 0.7349230647087097,
161
+ "eval_loss": 1.7473630905151367,
162
+ "eval_rouge1": 0.637439872504459,
163
+ "eval_rouge2": 0.34307164454056094,
164
+ "eval_rougeL": 0.5129717676228565,
165
+ "eval_rougeLsum": 0.6272190896182391,
166
+ "eval_runtime": 15.5672,
167
+ "eval_samples_per_second": 0.642,
168
+ "eval_steps_per_second": 0.321,
169
+ "step": 1600
170
+ },
171
+ {
172
+ "epoch": 0.21,
173
+ "grad_norm": 0.2025599479675293,
174
+ "learning_rate": 0.00018977411912154274,
175
+ "loss": 1.6721,
176
+ "step": 1800
177
+ },
178
+ {
179
+ "epoch": 0.21,
180
+ "eval_bertscore": 0.7357184290885925,
181
+ "eval_loss": 1.7516342401504517,
182
+ "eval_rouge1": 0.6387615819926658,
183
+ "eval_rouge2": 0.34366787517105574,
184
+ "eval_rougeL": 0.5129026911770751,
185
+ "eval_rougeLsum": 0.6289314118258257,
186
+ "eval_runtime": 15.9574,
187
+ "eval_samples_per_second": 0.627,
188
+ "eval_steps_per_second": 0.313,
189
+ "step": 1800
190
+ },
191
+ {
192
+ "epoch": 0.23,
193
+ "grad_norm": 0.20457112789154053,
194
+ "learning_rate": 0.0001886347452075085,
195
+ "loss": 1.671,
196
+ "step": 2000
197
+ },
198
+ {
199
+ "epoch": 0.23,
200
+ "eval_bertscore": 0.733718752861023,
201
+ "eval_loss": 1.7501707077026367,
202
+ "eval_rouge1": 0.6346207681220664,
203
+ "eval_rouge2": 0.33748369437614106,
204
+ "eval_rougeL": 0.5085159047705141,
205
+ "eval_rougeLsum": 0.6239953154441167,
206
+ "eval_runtime": 15.0863,
207
+ "eval_samples_per_second": 0.663,
208
+ "eval_steps_per_second": 0.331,
209
+ "step": 2000
210
+ },
211
+ {
212
+ "epoch": 0.25,
213
+ "grad_norm": 0.22552740573883057,
214
+ "learning_rate": 0.00018749537129347424,
215
+ "loss": 1.6496,
216
+ "step": 2200
217
+ },
218
+ {
219
+ "epoch": 0.25,
220
+ "eval_bertscore": 0.7368552684783936,
221
+ "eval_loss": 1.7437107563018799,
222
+ "eval_rouge1": 0.6490756387878311,
223
+ "eval_rouge2": 0.3448817738175175,
224
+ "eval_rougeL": 0.5235187045706321,
225
+ "eval_rougeLsum": 0.6377780857890332,
226
+ "eval_runtime": 15.07,
227
+ "eval_samples_per_second": 0.664,
228
+ "eval_steps_per_second": 0.332,
229
+ "step": 2200
230
+ },
231
+ {
232
+ "epoch": 0.27,
233
+ "grad_norm": 0.22573673725128174,
234
+ "learning_rate": 0.00018635599737944,
235
+ "loss": 1.6629,
236
+ "step": 2400
237
+ },
238
+ {
239
+ "epoch": 0.27,
240
+ "eval_bertscore": 0.7314499616622925,
241
+ "eval_loss": 1.7462828159332275,
242
+ "eval_rouge1": 0.6511482369678803,
243
+ "eval_rouge2": 0.34632544827771805,
244
+ "eval_rougeL": 0.5212417191003778,
245
+ "eval_rougeLsum": 0.6415391907940229,
246
+ "eval_runtime": 15.2078,
247
+ "eval_samples_per_second": 0.658,
248
+ "eval_steps_per_second": 0.329,
249
+ "step": 2400
250
+ },
251
+ {
252
+ "epoch": 0.3,
253
+ "grad_norm": 0.26426687836647034,
254
+ "learning_rate": 0.00018521662346540575,
255
+ "loss": 1.6644,
256
+ "step": 2600
257
+ },
258
+ {
259
+ "epoch": 0.3,
260
+ "eval_bertscore": 0.7363359928131104,
261
+ "eval_loss": 1.7505037784576416,
262
+ "eval_rouge1": 0.6498296552335481,
263
+ "eval_rouge2": 0.34873833589761183,
264
+ "eval_rougeL": 0.5194028620820592,
265
+ "eval_rougeLsum": 0.6404603087578984,
266
+ "eval_runtime": 14.8403,
267
+ "eval_samples_per_second": 0.674,
268
+ "eval_steps_per_second": 0.337,
269
+ "step": 2600
270
+ },
271
+ {
272
+ "epoch": 0.32,
273
+ "grad_norm": 0.20142091810703278,
274
+ "learning_rate": 0.00018407724955137153,
275
+ "loss": 1.6535,
276
+ "step": 2800
277
+ },
278
+ {
279
+ "epoch": 0.32,
280
+ "eval_bertscore": 0.7304679155349731,
281
+ "eval_loss": 1.7511039972305298,
282
+ "eval_rouge1": 0.6475130585388738,
283
+ "eval_rouge2": 0.34648331046897884,
284
+ "eval_rougeL": 0.5218042284020985,
285
+ "eval_rougeLsum": 0.6382749834402862,
286
+ "eval_runtime": 15.0162,
287
+ "eval_samples_per_second": 0.666,
288
+ "eval_steps_per_second": 0.333,
289
+ "step": 2800
290
+ },
291
+ {
292
+ "epoch": 0.34,
293
+ "grad_norm": 0.23283220827579498,
294
+ "learning_rate": 0.00018293787563733728,
295
+ "loss": 1.6477,
296
+ "step": 3000
297
+ },
298
+ {
299
+ "epoch": 0.34,
300
+ "eval_bertscore": 0.7327049374580383,
301
+ "eval_loss": 1.7461665868759155,
302
+ "eval_rouge1": 0.6309349586871908,
303
+ "eval_rouge2": 0.3387882478990309,
304
+ "eval_rougeL": 0.5042059192403674,
305
+ "eval_rougeLsum": 0.6210432469674847,
306
+ "eval_runtime": 15.463,
307
+ "eval_samples_per_second": 0.647,
308
+ "eval_steps_per_second": 0.323,
309
+ "step": 3000
310
+ },
311
+ {
312
+ "epoch": 0.36,
313
+ "grad_norm": 0.21316750347614288,
314
+ "learning_rate": 0.00018179850172330306,
315
+ "loss": 1.6614,
316
+ "step": 3200
317
+ },
318
+ {
319
+ "epoch": 0.36,
320
+ "eval_bertscore": 0.7314620018005371,
321
+ "eval_loss": 1.7468239068984985,
322
+ "eval_rouge1": 0.6480904534152265,
323
+ "eval_rouge2": 0.3479530168963481,
324
+ "eval_rougeL": 0.5193148273848067,
325
+ "eval_rougeLsum": 0.6366010767207634,
326
+ "eval_runtime": 15.0381,
327
+ "eval_samples_per_second": 0.665,
328
+ "eval_steps_per_second": 0.332,
329
+ "step": 3200
330
+ },
331
+ {
332
+ "epoch": 0.39,
333
+ "grad_norm": 0.26080408692359924,
334
+ "learning_rate": 0.00018065912780926882,
335
+ "loss": 1.6591,
336
+ "step": 3400
337
+ },
338
+ {
339
+ "epoch": 0.39,
340
+ "eval_bertscore": 0.7327477335929871,
341
+ "eval_loss": 1.7442594766616821,
342
+ "eval_rouge1": 0.6424613378037144,
343
+ "eval_rouge2": 0.34731770322974903,
344
+ "eval_rougeL": 0.5160705879794565,
345
+ "eval_rougeLsum": 0.6327006420281607,
346
+ "eval_runtime": 15.5373,
347
+ "eval_samples_per_second": 0.644,
348
+ "eval_steps_per_second": 0.322,
349
+ "step": 3400
350
+ },
351
+ {
352
+ "epoch": 0.41,
353
+ "grad_norm": 0.23274216055870056,
354
+ "learning_rate": 0.0001795197538952346,
355
+ "loss": 1.6613,
356
+ "step": 3600
357
+ },
358
+ {
359
+ "epoch": 0.41,
360
+ "eval_bertscore": 0.736956000328064,
361
+ "eval_loss": 1.7429373264312744,
362
+ "eval_rouge1": 0.6514574160666677,
363
+ "eval_rouge2": 0.3556199242231646,
364
+ "eval_rougeL": 0.5249726237675663,
365
+ "eval_rougeLsum": 0.6406261097623661,
366
+ "eval_runtime": 14.9415,
367
+ "eval_samples_per_second": 0.669,
368
+ "eval_steps_per_second": 0.335,
369
+ "step": 3600
370
+ },
371
+ {
372
+ "epoch": 0.43,
373
+ "grad_norm": 0.23616766929626465,
374
+ "learning_rate": 0.00017838037998120035,
375
+ "loss": 1.6479,
376
+ "step": 3800
377
+ },
378
+ {
379
+ "epoch": 0.43,
380
+ "eval_bertscore": 0.7349627614021301,
381
+ "eval_loss": 1.7420669794082642,
382
+ "eval_rouge1": 0.655851684949526,
383
+ "eval_rouge2": 0.35254590691865084,
384
+ "eval_rougeL": 0.5248980956621441,
385
+ "eval_rougeLsum": 0.6449637270581419,
386
+ "eval_runtime": 15.4178,
387
+ "eval_samples_per_second": 0.649,
388
+ "eval_steps_per_second": 0.324,
389
+ "step": 3800
390
+ },
391
+ {
392
+ "epoch": 0.46,
393
+ "grad_norm": 0.23260319232940674,
394
+ "learning_rate": 0.0001772410060671661,
395
+ "loss": 1.6569,
396
+ "step": 4000
397
+ },
398
+ {
399
+ "epoch": 0.46,
400
+ "eval_bertscore": 0.7332885265350342,
401
+ "eval_loss": 1.7401313781738281,
402
+ "eval_rouge1": 0.6669483634140105,
403
+ "eval_rouge2": 0.35873988835161297,
404
+ "eval_rougeL": 0.5343868725007427,
405
+ "eval_rougeLsum": 0.6555353134690931,
406
+ "eval_runtime": 15.0822,
407
+ "eval_samples_per_second": 0.663,
408
+ "eval_steps_per_second": 0.332,
409
+ "step": 4000
410
+ },
411
+ {
412
+ "epoch": 0.48,
413
+ "grad_norm": 0.2366473525762558,
414
+ "learning_rate": 0.00017610163215313186,
415
+ "loss": 1.6599,
416
+ "step": 4200
417
+ },
418
+ {
419
+ "epoch": 0.48,
420
+ "eval_bertscore": 0.7335314750671387,
421
+ "eval_loss": 1.7385823726654053,
422
+ "eval_rouge1": 0.6559297063578133,
423
+ "eval_rouge2": 0.35483499789990636,
424
+ "eval_rougeL": 0.5297939800986089,
425
+ "eval_rougeLsum": 0.6454544372491222,
426
+ "eval_runtime": 15.1029,
427
+ "eval_samples_per_second": 0.662,
428
+ "eval_steps_per_second": 0.331,
429
+ "step": 4200
430
+ },
431
+ {
432
+ "epoch": 0.5,
433
+ "grad_norm": 0.20628753304481506,
434
+ "learning_rate": 0.0001749622582390976,
435
+ "loss": 1.6454,
436
+ "step": 4400
437
+ },
438
+ {
439
+ "epoch": 0.5,
440
+ "eval_bertscore": 0.7342795133590698,
441
+ "eval_loss": 1.7422058582305908,
442
+ "eval_rouge1": 0.660746519614568,
443
+ "eval_rouge2": 0.3633965895561597,
444
+ "eval_rougeL": 0.5369036980876734,
445
+ "eval_rougeLsum": 0.650338328328998,
446
+ "eval_runtime": 15.4434,
447
+ "eval_samples_per_second": 0.648,
448
+ "eval_steps_per_second": 0.324,
449
+ "step": 4400
450
+ },
451
+ {
452
+ "epoch": 0.52,
453
+ "grad_norm": 0.2239149957895279,
454
+ "learning_rate": 0.0001738228843250634,
455
+ "loss": 1.6594,
456
+ "step": 4600
457
+ },
458
+ {
459
+ "epoch": 0.52,
460
+ "eval_bertscore": 0.7313543558120728,
461
+ "eval_loss": 1.740854263305664,
462
+ "eval_rouge1": 0.6591645132619427,
463
+ "eval_rouge2": 0.35766117432431743,
464
+ "eval_rougeL": 0.532710255034635,
465
+ "eval_rougeLsum": 0.6479428185884644,
466
+ "eval_runtime": 14.9436,
467
+ "eval_samples_per_second": 0.669,
468
+ "eval_steps_per_second": 0.335,
469
+ "step": 4600
470
+ },
471
+ {
472
+ "epoch": 0.55,
473
+ "grad_norm": 0.24808338284492493,
474
+ "learning_rate": 0.00017268351041102914,
475
+ "loss": 1.6604,
476
+ "step": 4800
477
+ },
478
+ {
479
+ "epoch": 0.55,
480
+ "eval_bertscore": 0.7333321571350098,
481
+ "eval_loss": 1.7385585308074951,
482
+ "eval_rouge1": 0.6532115808232871,
483
+ "eval_rouge2": 0.35333788022501567,
484
+ "eval_rougeL": 0.5284071547874328,
485
+ "eval_rougeLsum": 0.6410472452797623,
486
+ "eval_runtime": 15.0277,
487
+ "eval_samples_per_second": 0.665,
488
+ "eval_steps_per_second": 0.333,
489
+ "step": 4800
490
+ },
491
+ {
492
+ "epoch": 0.57,
493
+ "grad_norm": 0.2555364966392517,
494
+ "learning_rate": 0.0001715441364969949,
495
+ "loss": 1.6493,
496
+ "step": 5000
497
+ },
498
+ {
499
+ "epoch": 0.57,
500
+ "eval_bertscore": 0.7318152189254761,
501
+ "eval_loss": 1.7357494831085205,
502
+ "eval_rouge1": 0.6476755890502586,
503
+ "eval_rouge2": 0.35312778275949164,
504
+ "eval_rougeL": 0.5227601228049905,
505
+ "eval_rougeLsum": 0.6371331138372852,
506
+ "eval_runtime": 14.8807,
507
+ "eval_samples_per_second": 0.672,
508
+ "eval_steps_per_second": 0.336,
509
+ "step": 5000
510
+ },
511
+ {
512
+ "epoch": 0.59,
513
+ "grad_norm": 0.21518155932426453,
514
+ "learning_rate": 0.00017040476258296068,
515
+ "loss": 1.644,
516
+ "step": 5200
517
+ },
518
+ {
519
+ "epoch": 0.59,
520
+ "eval_bertscore": 0.734805703163147,
521
+ "eval_loss": 1.74032723903656,
522
+ "eval_rouge1": 0.6476813733451636,
523
+ "eval_rouge2": 0.3509259728617576,
524
+ "eval_rougeL": 0.5221334872800274,
525
+ "eval_rougeLsum": 0.636892384667733,
526
+ "eval_runtime": 15.1271,
527
+ "eval_samples_per_second": 0.661,
528
+ "eval_steps_per_second": 0.331,
529
+ "step": 5200
530
+ },
531
+ {
532
+ "epoch": 0.62,
533
+ "grad_norm": 0.26086658239364624,
534
+ "learning_rate": 0.00016926538866892643,
535
+ "loss": 1.6449,
536
+ "step": 5400
537
+ },
538
+ {
539
+ "epoch": 0.62,
540
+ "eval_bertscore": 0.7339995503425598,
541
+ "eval_loss": 1.7338205575942993,
542
+ "eval_rouge1": 0.6416889902864902,
543
+ "eval_rouge2": 0.3479045880347737,
544
+ "eval_rougeL": 0.5160577838468976,
545
+ "eval_rougeLsum": 0.6317983411796093,
546
+ "eval_runtime": 14.9992,
547
+ "eval_samples_per_second": 0.667,
548
+ "eval_steps_per_second": 0.333,
549
+ "step": 5400
550
+ },
551
+ {
552
+ "epoch": 0.64,
553
+ "grad_norm": 0.25449469685554504,
554
+ "learning_rate": 0.0001681260147548922,
555
+ "loss": 1.6299,
556
+ "step": 5600
557
+ },
558
+ {
559
+ "epoch": 0.64,
560
+ "eval_bertscore": 0.7306328415870667,
561
+ "eval_loss": 1.7369228601455688,
562
+ "eval_rouge1": 0.6390760905985684,
563
+ "eval_rouge2": 0.3409328272828699,
564
+ "eval_rougeL": 0.5111832543685331,
565
+ "eval_rougeLsum": 0.6285753423407665,
566
+ "eval_runtime": 15.483,
567
+ "eval_samples_per_second": 0.646,
568
+ "eval_steps_per_second": 0.323,
569
+ "step": 5600
570
+ },
571
+ {
572
+ "epoch": 0.66,
573
+ "grad_norm": 0.24706102907657623,
574
+ "learning_rate": 0.00016698664084085796,
575
+ "loss": 1.6374,
576
+ "step": 5800
577
+ },
578
+ {
579
+ "epoch": 0.66,
580
+ "eval_bertscore": 0.732075572013855,
581
+ "eval_loss": 1.7343876361846924,
582
+ "eval_rouge1": 0.6378821977913272,
583
+ "eval_rouge2": 0.34619427775171585,
584
+ "eval_rougeL": 0.5120186953041237,
585
+ "eval_rougeLsum": 0.6284056323839109,
586
+ "eval_runtime": 15.7341,
587
+ "eval_samples_per_second": 0.636,
588
+ "eval_steps_per_second": 0.318,
589
+ "step": 5800
590
+ },
591
+ {
592
+ "epoch": 0.68,
593
+ "grad_norm": 0.24373260140419006,
594
+ "learning_rate": 0.00016584726692682372,
595
+ "loss": 1.6427,
596
+ "step": 6000
597
+ },
598
+ {
599
+ "epoch": 0.68,
600
+ "eval_bertscore": 0.7350374460220337,
601
+ "eval_loss": 1.729591965675354,
602
+ "eval_rouge1": 0.6516545226356616,
603
+ "eval_rouge2": 0.35485762033878543,
604
+ "eval_rougeL": 0.5249054193354852,
605
+ "eval_rougeLsum": 0.6411016821651583,
606
+ "eval_runtime": 15.5199,
607
+ "eval_samples_per_second": 0.644,
608
+ "eval_steps_per_second": 0.322,
609
+ "step": 6000
610
+ },
611
+ {
612
+ "epoch": 0.71,
613
+ "grad_norm": 0.24616578221321106,
614
+ "learning_rate": 0.0001647078930127895,
615
+ "loss": 1.6296,
616
+ "step": 6200
617
+ },
618
+ {
619
+ "epoch": 0.71,
620
+ "eval_bertscore": 0.7335461378097534,
621
+ "eval_loss": 1.7302274703979492,
622
+ "eval_rouge1": 0.6531411706717427,
623
+ "eval_rouge2": 0.35003053174601517,
624
+ "eval_rougeL": 0.5212483686089053,
625
+ "eval_rougeLsum": 0.6438454124825417,
626
+ "eval_runtime": 15.3058,
627
+ "eval_samples_per_second": 0.653,
628
+ "eval_steps_per_second": 0.327,
629
+ "step": 6200
630
+ },
631
+ {
632
+ "epoch": 0.73,
633
+ "grad_norm": 0.24500492215156555,
634
+ "learning_rate": 0.00016356851909875522,
635
+ "loss": 1.6251,
636
+ "step": 6400
637
+ },
638
+ {
639
+ "epoch": 0.73,
640
+ "eval_bertscore": 0.7347471714019775,
641
+ "eval_loss": 1.7292228937149048,
642
+ "eval_rouge1": 0.6565322485502556,
643
+ "eval_rouge2": 0.35887540291607073,
644
+ "eval_rougeL": 0.5284326132878907,
645
+ "eval_rougeLsum": 0.6469750895866724,
646
+ "eval_runtime": 14.9708,
647
+ "eval_samples_per_second": 0.668,
648
+ "eval_steps_per_second": 0.334,
649
+ "step": 6400
650
+ },
651
+ {
652
+ "epoch": 0.75,
653
+ "grad_norm": 0.26575228571891785,
654
+ "learning_rate": 0.000162429145184721,
655
+ "loss": 1.6389,
656
+ "step": 6600
657
+ },
658
+ {
659
+ "epoch": 0.75,
660
+ "eval_bertscore": 0.7319897413253784,
661
+ "eval_loss": 1.7287580966949463,
662
+ "eval_rouge1": 0.6458608801881298,
663
+ "eval_rouge2": 0.3503480901452204,
664
+ "eval_rougeL": 0.519626708150005,
665
+ "eval_rougeLsum": 0.6362405734928169,
666
+ "eval_runtime": 15.3509,
667
+ "eval_samples_per_second": 0.651,
668
+ "eval_steps_per_second": 0.326,
669
+ "step": 6600
670
+ },
671
+ {
672
+ "epoch": 0.77,
673
+ "grad_norm": 0.27144965529441833,
674
+ "learning_rate": 0.00016128977127068676,
675
+ "loss": 1.6476,
676
+ "step": 6800
677
+ },
678
+ {
679
+ "epoch": 0.77,
680
+ "eval_bertscore": 0.7392772436141968,
681
+ "eval_loss": 1.7257907390594482,
682
+ "eval_rouge1": 0.6543238897579965,
683
+ "eval_rouge2": 0.3606726049451984,
684
+ "eval_rougeL": 0.5317585887753791,
685
+ "eval_rougeLsum": 0.6452028420624081,
686
+ "eval_runtime": 15.0268,
687
+ "eval_samples_per_second": 0.665,
688
+ "eval_steps_per_second": 0.333,
689
+ "step": 6800
690
+ },
691
+ {
692
+ "epoch": 0.8,
693
+ "grad_norm": 0.2579711079597473,
694
+ "learning_rate": 0.00016015039735665254,
695
+ "loss": 1.6316,
696
+ "step": 7000
697
+ },
698
+ {
699
+ "epoch": 0.8,
700
+ "eval_bertscore": 0.7375612854957581,
701
+ "eval_loss": 1.7296981811523438,
702
+ "eval_rouge1": 0.658906725408624,
703
+ "eval_rouge2": 0.35825094165644866,
704
+ "eval_rougeL": 0.5323299193377959,
705
+ "eval_rougeLsum": 0.6500364347290426,
706
+ "eval_runtime": 14.9244,
707
+ "eval_samples_per_second": 0.67,
708
+ "eval_steps_per_second": 0.335,
709
+ "step": 7000
710
+ },
711
+ {
712
+ "epoch": 0.82,
713
+ "grad_norm": 0.2589207589626312,
714
+ "learning_rate": 0.0001590110234426183,
715
+ "loss": 1.6432,
716
+ "step": 7200
717
+ },
718
+ {
719
+ "epoch": 0.82,
720
+ "eval_bertscore": 0.735145092010498,
721
+ "eval_loss": 1.72720205783844,
722
+ "eval_rouge1": 0.6678646250245518,
723
+ "eval_rouge2": 0.36332843150846983,
724
+ "eval_rougeL": 0.537576430733886,
725
+ "eval_rougeLsum": 0.6579789388660506,
726
+ "eval_runtime": 14.9067,
727
+ "eval_samples_per_second": 0.671,
728
+ "eval_steps_per_second": 0.335,
729
+ "step": 7200
730
+ },
731
+ {
732
+ "epoch": 0.84,
733
+ "grad_norm": 0.26652559638023376,
734
+ "learning_rate": 0.00015787164952858404,
735
+ "loss": 1.6488,
736
+ "step": 7400
737
+ },
738
+ {
739
+ "epoch": 0.84,
740
+ "eval_bertscore": 0.7320755124092102,
741
+ "eval_loss": 1.7282931804656982,
742
+ "eval_rouge1": 0.6325633297780734,
743
+ "eval_rouge2": 0.34505856555703185,
744
+ "eval_rougeL": 0.5100006743383693,
745
+ "eval_rougeLsum": 0.6230385336341938,
746
+ "eval_runtime": 14.9075,
747
+ "eval_samples_per_second": 0.671,
748
+ "eval_steps_per_second": 0.335,
749
+ "step": 7400
750
+ },
751
+ {
752
+ "epoch": 0.87,
753
+ "grad_norm": 0.27353721857070923,
754
+ "learning_rate": 0.00015673227561454982,
755
+ "loss": 1.6486,
756
+ "step": 7600
757
+ },
758
+ {
759
+ "epoch": 0.87,
760
+ "eval_bertscore": 0.7367390394210815,
761
+ "eval_loss": 1.7290785312652588,
762
+ "eval_rouge1": 0.639487116874423,
763
+ "eval_rouge2": 0.3466574229736927,
764
+ "eval_rougeL": 0.515038120249177,
765
+ "eval_rougeLsum": 0.6301157215372983,
766
+ "eval_runtime": 15.0876,
767
+ "eval_samples_per_second": 0.663,
768
+ "eval_steps_per_second": 0.331,
769
+ "step": 7600
770
+ },
771
+ {
772
+ "epoch": 0.89,
773
+ "grad_norm": 0.24777938425540924,
774
+ "learning_rate": 0.00015559290170051558,
775
+ "loss": 1.6271,
776
+ "step": 7800
777
+ },
778
+ {
779
+ "epoch": 0.89,
780
+ "eval_bertscore": 0.735866904258728,
781
+ "eval_loss": 1.7264015674591064,
782
+ "eval_rouge1": 0.64939597901302,
783
+ "eval_rouge2": 0.3554282813944538,
784
+ "eval_rougeL": 0.5247953329477759,
785
+ "eval_rougeLsum": 0.6405524812915908,
786
+ "eval_runtime": 14.8892,
787
+ "eval_samples_per_second": 0.672,
788
+ "eval_steps_per_second": 0.336,
789
+ "step": 7800
790
+ },
791
+ {
792
+ "epoch": 0.91,
793
+ "grad_norm": 0.2703794538974762,
794
+ "learning_rate": 0.00015445352778648136,
795
+ "loss": 1.6415,
796
+ "step": 8000
797
+ },
798
+ {
799
+ "epoch": 0.91,
800
+ "eval_bertscore": 0.7325771450996399,
801
+ "eval_loss": 1.7271970510482788,
802
+ "eval_rouge1": 0.6659432894288253,
803
+ "eval_rouge2": 0.35962933912652617,
804
+ "eval_rougeL": 0.5385420432813512,
805
+ "eval_rougeLsum": 0.6557027031484046,
806
+ "eval_runtime": 14.8319,
807
+ "eval_samples_per_second": 0.674,
808
+ "eval_steps_per_second": 0.337,
809
+ "step": 8000
810
+ },
811
+ {
812
+ "epoch": 0.93,
813
+ "grad_norm": 0.28753793239593506,
814
+ "learning_rate": 0.0001533141538724471,
815
+ "loss": 1.6239,
816
+ "step": 8200
817
+ },
818
+ {
819
+ "epoch": 0.93,
820
+ "eval_bertscore": 0.7350013852119446,
821
+ "eval_loss": 1.7266199588775635,
822
+ "eval_rouge1": 0.6549282561414593,
823
+ "eval_rouge2": 0.35694530595734475,
824
+ "eval_rougeL": 0.5301601006964574,
825
+ "eval_rougeLsum": 0.6441779306137909,
826
+ "eval_runtime": 14.9005,
827
+ "eval_samples_per_second": 0.671,
828
+ "eval_steps_per_second": 0.336,
829
+ "step": 8200
830
+ },
831
+ {
832
+ "epoch": 0.96,
833
+ "grad_norm": 0.23870150744915009,
834
+ "learning_rate": 0.00015217477995841286,
835
+ "loss": 1.6293,
836
+ "step": 8400
837
+ },
838
+ {
839
+ "epoch": 0.96,
840
+ "eval_bertscore": 0.7271261811256409,
841
+ "eval_loss": 1.7256368398666382,
842
+ "eval_rouge1": 0.6515513829901936,
843
+ "eval_rouge2": 0.35217616104918836,
844
+ "eval_rougeL": 0.5236553509227138,
845
+ "eval_rougeLsum": 0.6411473505324752,
846
+ "eval_runtime": 14.9938,
847
+ "eval_samples_per_second": 0.667,
848
+ "eval_steps_per_second": 0.333,
849
+ "step": 8400
850
+ },
851
+ {
852
+ "epoch": 0.98,
853
+ "grad_norm": 0.28276997804641724,
854
+ "learning_rate": 0.00015103540604437861,
855
+ "loss": 1.6242,
856
+ "step": 8600
857
+ },
858
+ {
859
+ "epoch": 0.98,
860
+ "eval_bertscore": 0.7347334027290344,
861
+ "eval_loss": 1.717627763748169,
862
+ "eval_rouge1": 0.6350112495847634,
863
+ "eval_rouge2": 0.3477570751550898,
864
+ "eval_rougeL": 0.5146616989899861,
865
+ "eval_rougeLsum": 0.6246669376525157,
866
+ "eval_runtime": 15.7032,
867
+ "eval_samples_per_second": 0.637,
868
+ "eval_steps_per_second": 0.318,
869
+ "step": 8600
870
+ },
871
+ {
872
+ "epoch": 1.0,
873
+ "grad_norm": 0.24915842711925507,
874
+ "learning_rate": 0.00014989603213034437,
875
+ "loss": 1.6245,
876
+ "step": 8800
877
+ },
878
+ {
879
+ "epoch": 1.0,
880
+ "eval_bertscore": 0.7313701510429382,
881
+ "eval_loss": 1.7292964458465576,
882
+ "eval_rouge1": 0.6479528105367669,
883
+ "eval_rouge2": 0.35020983244262877,
884
+ "eval_rougeL": 0.5200907337780047,
885
+ "eval_rougeLsum": 0.6372896614836894,
886
+ "eval_runtime": 15.0043,
887
+ "eval_samples_per_second": 0.666,
888
+ "eval_steps_per_second": 0.333,
889
+ "step": 8800
890
+ },
891
+ {
892
+ "epoch": 1.03,
893
+ "grad_norm": 0.24036027491092682,
894
+ "learning_rate": 0.00014875665821631015,
895
+ "loss": 1.5364,
896
+ "step": 9000
897
+ },
898
+ {
899
+ "epoch": 1.03,
900
+ "eval_bertscore": 0.7327737808227539,
901
+ "eval_loss": 1.7339435815811157,
902
+ "eval_rouge1": 0.6568524178922349,
903
+ "eval_rouge2": 0.35560270713543163,
904
+ "eval_rougeL": 0.5310443670833082,
905
+ "eval_rougeLsum": 0.6480993679097387,
906
+ "eval_runtime": 14.9303,
907
+ "eval_samples_per_second": 0.67,
908
+ "eval_steps_per_second": 0.335,
909
+ "step": 9000
910
+ },
911
+ {
912
+ "epoch": 1.05,
913
+ "grad_norm": 0.2729027271270752,
914
+ "learning_rate": 0.0001476172843022759,
915
+ "loss": 1.5182,
916
+ "step": 9200
917
+ },
918
+ {
919
+ "epoch": 1.05,
920
+ "eval_bertscore": 0.7334672212600708,
921
+ "eval_loss": 1.739061713218689,
922
+ "eval_rouge1": 0.6552962187824329,
923
+ "eval_rouge2": 0.35210314124279196,
924
+ "eval_rougeL": 0.5272039052368354,
925
+ "eval_rougeLsum": 0.6437473533492806,
926
+ "eval_runtime": 15.5418,
927
+ "eval_samples_per_second": 0.643,
928
+ "eval_steps_per_second": 0.322,
929
+ "step": 9200
930
+ },
931
+ {
932
+ "epoch": 1.07,
933
+ "grad_norm": 0.2909716069698334,
934
+ "learning_rate": 0.00014647791038824168,
935
+ "loss": 1.5276,
936
+ "step": 9400
937
+ },
938
+ {
939
+ "epoch": 1.07,
940
+ "eval_bertscore": 0.7288902997970581,
941
+ "eval_loss": 1.736944556236267,
942
+ "eval_rouge1": 0.6533271685598301,
943
+ "eval_rouge2": 0.35279315321532184,
944
+ "eval_rougeL": 0.5262688234671329,
945
+ "eval_rougeLsum": 0.6424084937151033,
946
+ "eval_runtime": 15.1115,
947
+ "eval_samples_per_second": 0.662,
948
+ "eval_steps_per_second": 0.331,
949
+ "step": 9400
950
+ },
951
+ {
952
+ "epoch": 1.09,
953
+ "grad_norm": 0.3035859763622284,
954
+ "learning_rate": 0.00014533853647420743,
955
+ "loss": 1.5445,
956
+ "step": 9600
957
+ },
958
+ {
959
+ "epoch": 1.09,
960
+ "eval_bertscore": 0.7308284044265747,
961
+ "eval_loss": 1.737762689590454,
962
+ "eval_rouge1": 0.6619725777891359,
963
+ "eval_rouge2": 0.3611963714506864,
964
+ "eval_rougeL": 0.5363802967084452,
965
+ "eval_rougeLsum": 0.6516690557971352,
966
+ "eval_runtime": 14.9932,
967
+ "eval_samples_per_second": 0.667,
968
+ "eval_steps_per_second": 0.333,
969
+ "step": 9600
970
+ },
971
+ {
972
+ "epoch": 1.12,
973
+ "grad_norm": 0.26574915647506714,
974
+ "learning_rate": 0.0001441991625601732,
975
+ "loss": 1.5342,
976
+ "step": 9800
977
+ },
978
+ {
979
+ "epoch": 1.12,
980
+ "eval_bertscore": 0.7328712344169617,
981
+ "eval_loss": 1.7393991947174072,
982
+ "eval_rouge1": 0.6856504003396884,
983
+ "eval_rouge2": 0.3761098841062477,
984
+ "eval_rougeL": 0.555477293163325,
985
+ "eval_rougeLsum": 0.6757574283262289,
986
+ "eval_runtime": 14.8121,
987
+ "eval_samples_per_second": 0.675,
988
+ "eval_steps_per_second": 0.338,
989
+ "step": 9800
990
+ },
991
+ {
992
+ "epoch": 1.14,
993
+ "grad_norm": 0.315468430519104,
994
+ "learning_rate": 0.00014305978864613897,
995
+ "loss": 1.543,
996
+ "step": 10000
997
+ },
998
+ {
999
+ "epoch": 1.14,
1000
+ "eval_bertscore": 0.7349387407302856,
1001
+ "eval_loss": 1.7352710962295532,
1002
+ "eval_rouge1": 0.6749953128982036,
1003
+ "eval_rouge2": 0.3720385250530084,
1004
+ "eval_rougeL": 0.5472261566474382,
1005
+ "eval_rougeLsum": 0.6657643539219252,
1006
+ "eval_runtime": 14.909,
1007
+ "eval_samples_per_second": 0.671,
1008
+ "eval_steps_per_second": 0.335,
1009
+ "step": 10000
1010
+ },
1011
+ {
1012
+ "epoch": 1.16,
1013
+ "grad_norm": 0.29815027117729187,
1014
+ "learning_rate": 0.00014192041473210472,
1015
+ "loss": 1.5547,
1016
+ "step": 10200
1017
+ },
1018
+ {
1019
+ "epoch": 1.16,
1020
+ "eval_bertscore": 0.7359883189201355,
1021
+ "eval_loss": 1.7269136905670166,
1022
+ "eval_rouge1": 0.6561141614088863,
1023
+ "eval_rouge2": 0.3606175666303814,
1024
+ "eval_rougeL": 0.5302270771032793,
1025
+ "eval_rougeLsum": 0.6446912079521883,
1026
+ "eval_runtime": 14.9527,
1027
+ "eval_samples_per_second": 0.669,
1028
+ "eval_steps_per_second": 0.334,
1029
+ "step": 10200
1030
+ },
1031
+ {
1032
+ "epoch": 1.18,
1033
+ "grad_norm": 0.3595702350139618,
1034
+ "learning_rate": 0.00014078104081807047,
1035
+ "loss": 1.5567,
1036
+ "step": 10400
1037
+ },
1038
+ {
1039
+ "epoch": 1.18,
1040
+ "eval_bertscore": 0.7328116297721863,
1041
+ "eval_loss": 1.7341644763946533,
1042
+ "eval_rouge1": 0.6420332714823549,
1043
+ "eval_rouge2": 0.35094864549032,
1044
+ "eval_rougeL": 0.5179556761398367,
1045
+ "eval_rougeLsum": 0.631987397226809,
1046
+ "eval_runtime": 15.1438,
1047
+ "eval_samples_per_second": 0.66,
1048
+ "eval_steps_per_second": 0.33,
1049
+ "step": 10400
1050
+ },
1051
+ {
1052
+ "epoch": 1.21,
1053
+ "grad_norm": 0.2718666195869446,
1054
+ "learning_rate": 0.00013964166690403623,
1055
+ "loss": 1.5408,
1056
+ "step": 10600
1057
+ },
1058
+ {
1059
+ "epoch": 1.21,
1060
+ "eval_bertscore": 0.7337731122970581,
1061
+ "eval_loss": 1.7330901622772217,
1062
+ "eval_rouge1": 0.661681342484687,
1063
+ "eval_rouge2": 0.3626833509973693,
1064
+ "eval_rougeL": 0.5329424447373774,
1065
+ "eval_rougeLsum": 0.6519750177144633,
1066
+ "eval_runtime": 14.8142,
1067
+ "eval_samples_per_second": 0.675,
1068
+ "eval_steps_per_second": 0.338,
1069
+ "step": 10600
1070
+ },
1071
+ {
1072
+ "epoch": 1.23,
1073
+ "grad_norm": 0.29183274507522583,
1074
+ "learning_rate": 0.00013850229299000198,
1075
+ "loss": 1.5422,
1076
+ "step": 10800
1077
+ },
1078
+ {
1079
+ "epoch": 1.23,
1080
+ "eval_bertscore": 0.7331051230430603,
1081
+ "eval_loss": 1.7297636270523071,
1082
+ "eval_rouge1": 0.6655497978238063,
1083
+ "eval_rouge2": 0.3614235788441926,
1084
+ "eval_rougeL": 0.5327210061667442,
1085
+ "eval_rougeLsum": 0.6548836840483913,
1086
+ "eval_runtime": 15.1359,
1087
+ "eval_samples_per_second": 0.661,
1088
+ "eval_steps_per_second": 0.33,
1089
+ "step": 10800
1090
+ },
1091
+ {
1092
+ "epoch": 1.25,
1093
+ "grad_norm": 0.30979740619659424,
1094
+ "learning_rate": 0.00013736291907596776,
1095
+ "loss": 1.5372,
1096
+ "step": 11000
1097
+ },
1098
+ {
1099
+ "epoch": 1.25,
1100
+ "eval_bertscore": 0.7312799692153931,
1101
+ "eval_loss": 1.732444167137146,
1102
+ "eval_rouge1": 0.6568292865033993,
1103
+ "eval_rouge2": 0.35876682221562006,
1104
+ "eval_rougeL": 0.5300878844981931,
1105
+ "eval_rougeLsum": 0.6461751645858989,
1106
+ "eval_runtime": 14.819,
1107
+ "eval_samples_per_second": 0.675,
1108
+ "eval_steps_per_second": 0.337,
1109
+ "step": 11000
1110
+ },
1111
+ {
1112
+ "epoch": 1.28,
1113
+ "grad_norm": 0.31343138217926025,
1114
+ "learning_rate": 0.0001362235451619335,
1115
+ "loss": 1.5301,
1116
+ "step": 11200
1117
+ },
1118
+ {
1119
+ "epoch": 1.28,
1120
+ "eval_bertscore": 0.7317885160446167,
1121
+ "eval_loss": 1.7358499765396118,
1122
+ "eval_rouge1": 0.6548673097943329,
1123
+ "eval_rouge2": 0.3609116081432997,
1124
+ "eval_rougeL": 0.5279887650752133,
1125
+ "eval_rougeLsum": 0.6466232329097188,
1126
+ "eval_runtime": 14.8259,
1127
+ "eval_samples_per_second": 0.674,
1128
+ "eval_steps_per_second": 0.337,
1129
+ "step": 11200
1130
+ },
1131
+ {
1132
+ "epoch": 1.3,
1133
+ "grad_norm": 0.36181533336639404,
1134
+ "learning_rate": 0.0001350841712478993,
1135
+ "loss": 1.5421,
1136
+ "step": 11400
1137
+ },
1138
+ {
1139
+ "epoch": 1.3,
1140
+ "eval_bertscore": 0.7316756248474121,
1141
+ "eval_loss": 1.7282969951629639,
1142
+ "eval_rouge1": 0.6551882964480251,
1143
+ "eval_rouge2": 0.3580708921400697,
1144
+ "eval_rougeL": 0.5255367305995147,
1145
+ "eval_rougeLsum": 0.6449192953008009,
1146
+ "eval_runtime": 14.8816,
1147
+ "eval_samples_per_second": 0.672,
1148
+ "eval_steps_per_second": 0.336,
1149
+ "step": 11400
1150
+ },
1151
+ {
1152
+ "epoch": 1.32,
1153
+ "grad_norm": 0.30600836873054504,
1154
+ "learning_rate": 0.00013394479733386505,
1155
+ "loss": 1.5538,
1156
+ "step": 11600
1157
+ },
1158
+ {
1159
+ "epoch": 1.32,
1160
+ "eval_bertscore": 0.7311854362487793,
1161
+ "eval_loss": 1.7313562631607056,
1162
+ "eval_rouge1": 0.6592751199424156,
1163
+ "eval_rouge2": 0.35802855072854206,
1164
+ "eval_rougeL": 0.5297288176377084,
1165
+ "eval_rougeLsum": 0.6489455314962717,
1166
+ "eval_runtime": 15.0693,
1167
+ "eval_samples_per_second": 0.664,
1168
+ "eval_steps_per_second": 0.332,
1169
+ "step": 11600
1170
+ },
1171
+ {
1172
+ "epoch": 1.34,
1173
+ "grad_norm": 0.29904893040657043,
1174
+ "learning_rate": 0.0001328054234198308,
1175
+ "loss": 1.5328,
1176
+ "step": 11800
1177
+ },
1178
+ {
1179
+ "epoch": 1.34,
1180
+ "eval_bertscore": 0.7312635183334351,
1181
+ "eval_loss": 1.7318429946899414,
1182
+ "eval_rouge1": 0.6577169369077195,
1183
+ "eval_rouge2": 0.3582474830918887,
1184
+ "eval_rougeL": 0.5314990647771975,
1185
+ "eval_rougeLsum": 0.6454785220479866,
1186
+ "eval_runtime": 15.0235,
1187
+ "eval_samples_per_second": 0.666,
1188
+ "eval_steps_per_second": 0.333,
1189
+ "step": 11800
1190
+ },
1191
+ {
1192
+ "epoch": 1.37,
1193
+ "grad_norm": 0.3025416433811188,
1194
+ "learning_rate": 0.00013166604950579658,
1195
+ "loss": 1.5349,
1196
+ "step": 12000
1197
+ },
1198
+ {
1199
+ "epoch": 1.37,
1200
+ "eval_bertscore": 0.7325812578201294,
1201
+ "eval_loss": 1.7309118509292603,
1202
+ "eval_rouge1": 0.6629133074951261,
1203
+ "eval_rouge2": 0.3678158453940578,
1204
+ "eval_rougeL": 0.5380936907276155,
1205
+ "eval_rougeLsum": 0.654883061928214,
1206
+ "eval_runtime": 14.7666,
1207
+ "eval_samples_per_second": 0.677,
1208
+ "eval_steps_per_second": 0.339,
1209
+ "step": 12000
1210
+ },
1211
+ {
1212
+ "epoch": 1.39,
1213
+ "grad_norm": 0.34982389211654663,
1214
+ "learning_rate": 0.00013052667559176233,
1215
+ "loss": 1.5513,
1216
+ "step": 12200
1217
+ },
1218
+ {
1219
+ "epoch": 1.39,
1220
+ "eval_bertscore": 0.7340582609176636,
1221
+ "eval_loss": 1.7363474369049072,
1222
+ "eval_rouge1": 0.6555817937418287,
1223
+ "eval_rouge2": 0.35630500078358396,
1224
+ "eval_rougeL": 0.5272412353478366,
1225
+ "eval_rougeLsum": 0.6445837479327643,
1226
+ "eval_runtime": 14.9664,
1227
+ "eval_samples_per_second": 0.668,
1228
+ "eval_steps_per_second": 0.334,
1229
+ "step": 12200
1230
+ },
1231
+ {
1232
+ "epoch": 1.41,
1233
+ "grad_norm": 0.35809043049812317,
1234
+ "learning_rate": 0.0001293873016777281,
1235
+ "loss": 1.5444,
1236
+ "step": 12400
1237
+ },
1238
+ {
1239
+ "epoch": 1.41,
1240
+ "eval_bertscore": 0.7334069013595581,
1241
+ "eval_loss": 1.7328729629516602,
1242
+ "eval_rouge1": 0.6617971237669364,
1243
+ "eval_rouge2": 0.35951260376512423,
1244
+ "eval_rougeL": 0.5345512305507059,
1245
+ "eval_rougeLsum": 0.648363531132752,
1246
+ "eval_runtime": 15.2146,
1247
+ "eval_samples_per_second": 0.657,
1248
+ "eval_steps_per_second": 0.329,
1249
+ "step": 12400
1250
+ },
1251
+ {
1252
+ "epoch": 1.44,
1253
+ "grad_norm": 0.2954196631908417,
1254
+ "learning_rate": 0.00012824792776369387,
1255
+ "loss": 1.5406,
1256
+ "step": 12600
1257
+ },
1258
+ {
1259
+ "epoch": 1.44,
1260
+ "eval_bertscore": 0.7321678400039673,
1261
+ "eval_loss": 1.7335160970687866,
1262
+ "eval_rouge1": 0.6573625593086756,
1263
+ "eval_rouge2": 0.36210525247389347,
1264
+ "eval_rougeL": 0.5379361120230158,
1265
+ "eval_rougeLsum": 0.6459787883452857,
1266
+ "eval_runtime": 14.8942,
1267
+ "eval_samples_per_second": 0.671,
1268
+ "eval_steps_per_second": 0.336,
1269
+ "step": 12600
1270
+ },
1271
+ {
1272
+ "epoch": 1.46,
1273
+ "grad_norm": 0.32190588116645813,
1274
+ "learning_rate": 0.00012710855384965962,
1275
+ "loss": 1.5491,
1276
+ "step": 12800
1277
+ },
1278
+ {
1279
+ "epoch": 1.46,
1280
+ "eval_bertscore": 0.7346011400222778,
1281
+ "eval_loss": 1.7364966869354248,
1282
+ "eval_rouge1": 0.6481210247390559,
1283
+ "eval_rouge2": 0.3521173896017687,
1284
+ "eval_rougeL": 0.5240500581372636,
1285
+ "eval_rougeLsum": 0.63706442433335,
1286
+ "eval_runtime": 14.923,
1287
+ "eval_samples_per_second": 0.67,
1288
+ "eval_steps_per_second": 0.335,
1289
+ "step": 12800
1290
+ },
1291
+ {
1292
+ "epoch": 1.48,
1293
+ "grad_norm": 0.33323267102241516,
1294
+ "learning_rate": 0.00012596917993562537,
1295
+ "loss": 1.5596,
1296
+ "step": 13000
1297
+ },
1298
+ {
1299
+ "epoch": 1.48,
1300
+ "eval_bertscore": 0.7331587076187134,
1301
+ "eval_loss": 1.7332260608673096,
1302
+ "eval_rouge1": 0.6561257401878793,
1303
+ "eval_rouge2": 0.3548063723792664,
1304
+ "eval_rougeL": 0.527807776001489,
1305
+ "eval_rougeLsum": 0.6451911907984706,
1306
+ "eval_runtime": 15.4703,
1307
+ "eval_samples_per_second": 0.646,
1308
+ "eval_steps_per_second": 0.323,
1309
+ "step": 13000
1310
+ },
1311
+ {
1312
+ "epoch": 1.5,
1313
+ "grad_norm": 0.3564057946205139,
1314
+ "learning_rate": 0.00012482980602159113,
1315
+ "loss": 1.5261,
1316
+ "step": 13200
1317
+ },
1318
+ {
1319
+ "epoch": 1.5,
1320
+ "eval_bertscore": 0.7306063771247864,
1321
+ "eval_loss": 1.7368810176849365,
1322
+ "eval_rouge1": 0.637722723890071,
1323
+ "eval_rouge2": 0.3455358728458236,
1324
+ "eval_rougeL": 0.5136372690435154,
1325
+ "eval_rougeLsum": 0.6273570573595115,
1326
+ "eval_runtime": 15.3533,
1327
+ "eval_samples_per_second": 0.651,
1328
+ "eval_steps_per_second": 0.326,
1329
+ "step": 13200
1330
+ },
1331
+ {
1332
+ "epoch": 1.53,
1333
+ "grad_norm": 0.29219934344291687,
1334
+ "learning_rate": 0.0001236904321075569,
1335
+ "loss": 1.519,
1336
+ "step": 13400
1337
+ },
1338
+ {
1339
+ "epoch": 1.53,
1340
+ "eval_bertscore": 0.7338696122169495,
1341
+ "eval_loss": 1.734724998474121,
1342
+ "eval_rouge1": 0.6442107446420164,
1343
+ "eval_rouge2": 0.3494748457109431,
1344
+ "eval_rougeL": 0.5207483892007314,
1345
+ "eval_rougeLsum": 0.632886404907802,
1346
+ "eval_runtime": 15.3077,
1347
+ "eval_samples_per_second": 0.653,
1348
+ "eval_steps_per_second": 0.327,
1349
+ "step": 13400
1350
+ },
1351
+ {
1352
+ "epoch": 1.55,
1353
+ "grad_norm": 0.34681758284568787,
1354
+ "learning_rate": 0.00012255105819352266,
1355
+ "loss": 1.5419,
1356
+ "step": 13600
1357
+ },
1358
+ {
1359
+ "epoch": 1.55,
1360
+ "eval_bertscore": 0.7350045442581177,
1361
+ "eval_loss": 1.7329858541488647,
1362
+ "eval_rouge1": 0.6606839869796519,
1363
+ "eval_rouge2": 0.362188561160822,
1364
+ "eval_rougeL": 0.5342033818317451,
1365
+ "eval_rougeLsum": 0.6493340000068861,
1366
+ "eval_runtime": 15.44,
1367
+ "eval_samples_per_second": 0.648,
1368
+ "eval_steps_per_second": 0.324,
1369
+ "step": 13600
1370
+ },
1371
+ {
1372
+ "epoch": 1.57,
1373
+ "grad_norm": 0.3043666481971741,
1374
+ "learning_rate": 0.00012141168427948844,
1375
+ "loss": 1.5402,
1376
+ "step": 13800
1377
+ },
1378
+ {
1379
+ "epoch": 1.57,
1380
+ "eval_bertscore": 0.7363221645355225,
1381
+ "eval_loss": 1.7308530807495117,
1382
+ "eval_rouge1": 0.6638252384356028,
1383
+ "eval_rouge2": 0.3643237697892826,
1384
+ "eval_rougeL": 0.5403775887381331,
1385
+ "eval_rougeLsum": 0.6537260000827279,
1386
+ "eval_runtime": 14.7668,
1387
+ "eval_samples_per_second": 0.677,
1388
+ "eval_steps_per_second": 0.339,
1389
+ "step": 13800
1390
+ },
1391
+ {
1392
+ "epoch": 1.59,
1393
+ "grad_norm": 0.4073585867881775,
1394
+ "learning_rate": 0.00012027231036545419,
1395
+ "loss": 1.5256,
1396
+ "step": 14000
1397
+ },
1398
+ {
1399
+ "epoch": 1.59,
1400
+ "eval_bertscore": 0.7310279607772827,
1401
+ "eval_loss": 1.7326784133911133,
1402
+ "eval_rouge1": 0.6609594314120198,
1403
+ "eval_rouge2": 0.3601530714440473,
1404
+ "eval_rougeL": 0.5344452687135626,
1405
+ "eval_rougeLsum": 0.6480936554342305,
1406
+ "eval_runtime": 14.8565,
1407
+ "eval_samples_per_second": 0.673,
1408
+ "eval_steps_per_second": 0.337,
1409
+ "step": 14000
1410
+ },
1411
+ {
1412
+ "epoch": 1.62,
1413
+ "grad_norm": 0.3211813271045685,
1414
+ "learning_rate": 0.00011913293645141995,
1415
+ "loss": 1.5366,
1416
+ "step": 14200
1417
+ },
1418
+ {
1419
+ "epoch": 1.62,
1420
+ "eval_bertscore": 0.7356667518615723,
1421
+ "eval_loss": 1.7280094623565674,
1422
+ "eval_rouge1": 0.6519353227375031,
1423
+ "eval_rouge2": 0.3587025716186173,
1424
+ "eval_rougeL": 0.5306356200586075,
1425
+ "eval_rougeLsum": 0.6408870347994059,
1426
+ "eval_runtime": 14.9264,
1427
+ "eval_samples_per_second": 0.67,
1428
+ "eval_steps_per_second": 0.335,
1429
+ "step": 14200
1430
+ },
1431
+ {
1432
+ "epoch": 1.64,
1433
+ "grad_norm": 0.32776832580566406,
1434
+ "learning_rate": 0.00011799356253738571,
1435
+ "loss": 1.5504,
1436
+ "step": 14400
1437
+ },
1438
+ {
1439
+ "epoch": 1.64,
1440
+ "eval_bertscore": 0.7331353425979614,
1441
+ "eval_loss": 1.7308950424194336,
1442
+ "eval_rouge1": 0.6627702292814652,
1443
+ "eval_rouge2": 0.36117793957379707,
1444
+ "eval_rougeL": 0.5369305446079228,
1445
+ "eval_rougeLsum": 0.6516924083980089,
1446
+ "eval_runtime": 16.0138,
1447
+ "eval_samples_per_second": 0.624,
1448
+ "eval_steps_per_second": 0.312,
1449
+ "step": 14400
1450
+ },
1451
+ {
1452
+ "epoch": 1.66,
1453
+ "grad_norm": 0.3209726810455322,
1454
+ "learning_rate": 0.00011685418862335147,
1455
+ "loss": 1.5473,
1456
+ "step": 14600
1457
+ },
1458
+ {
1459
+ "epoch": 1.66,
1460
+ "eval_bertscore": 0.732498824596405,
1461
+ "eval_loss": 1.7328402996063232,
1462
+ "eval_rouge1": 0.6482679740803596,
1463
+ "eval_rouge2": 0.3538726087405498,
1464
+ "eval_rougeL": 0.5267677183598017,
1465
+ "eval_rougeLsum": 0.6366529460029322,
1466
+ "eval_runtime": 15.0195,
1467
+ "eval_samples_per_second": 0.666,
1468
+ "eval_steps_per_second": 0.333,
1469
+ "step": 14600
1470
+ },
1471
+ {
1472
+ "epoch": 1.69,
1473
+ "grad_norm": 0.3174591064453125,
1474
+ "learning_rate": 0.00011571481470931725,
1475
+ "loss": 1.5568,
1476
+ "step": 14800
1477
+ },
1478
+ {
1479
+ "epoch": 1.69,
1480
+ "eval_bertscore": 0.7335298657417297,
1481
+ "eval_loss": 1.7310253381729126,
1482
+ "eval_rouge1": 0.6560468577439627,
1483
+ "eval_rouge2": 0.36039371229175,
1484
+ "eval_rougeL": 0.5318708569729291,
1485
+ "eval_rougeLsum": 0.6444857558837042,
1486
+ "eval_runtime": 14.9774,
1487
+ "eval_samples_per_second": 0.668,
1488
+ "eval_steps_per_second": 0.334,
1489
+ "step": 14800
1490
+ },
1491
+ {
1492
+ "epoch": 1.71,
1493
+ "grad_norm": 0.2936408817768097,
1494
+ "learning_rate": 0.000114575440795283,
1495
+ "loss": 1.5345,
1496
+ "step": 15000
1497
+ },
1498
+ {
1499
+ "epoch": 1.71,
1500
+ "eval_bertscore": 0.7322725057601929,
1501
+ "eval_loss": 1.7270629405975342,
1502
+ "eval_rouge1": 0.6387060930656672,
1503
+ "eval_rouge2": 0.3480508127989137,
1504
+ "eval_rougeL": 0.5148670834213287,
1505
+ "eval_rougeLsum": 0.6273654952601909,
1506
+ "eval_runtime": 15.6687,
1507
+ "eval_samples_per_second": 0.638,
1508
+ "eval_steps_per_second": 0.319,
1509
+ "step": 15000
1510
+ },
1511
+ {
1512
+ "epoch": 1.73,
1513
+ "grad_norm": 0.32960689067840576,
1514
+ "learning_rate": 0.00011343606688124875,
1515
+ "loss": 1.5362,
1516
+ "step": 15200
1517
+ },
1518
+ {
1519
+ "epoch": 1.73,
1520
+ "eval_bertscore": 0.7337037920951843,
1521
+ "eval_loss": 1.7287395000457764,
1522
+ "eval_rouge1": 0.6476816970229771,
1523
+ "eval_rouge2": 0.3532248216683249,
1524
+ "eval_rougeL": 0.5253136618838716,
1525
+ "eval_rougeLsum": 0.6347493764394183,
1526
+ "eval_runtime": 15.0045,
1527
+ "eval_samples_per_second": 0.666,
1528
+ "eval_steps_per_second": 0.333,
1529
+ "step": 15200
1530
+ },
1531
+ {
1532
+ "epoch": 1.75,
1533
+ "grad_norm": 0.33265602588653564,
1534
+ "learning_rate": 0.00011229669296721452,
1535
+ "loss": 1.5215,
1536
+ "step": 15400
1537
+ },
1538
+ {
1539
+ "epoch": 1.75,
1540
+ "eval_bertscore": 0.7330806851387024,
1541
+ "eval_loss": 1.7265052795410156,
1542
+ "eval_rouge1": 0.6529393512177359,
1543
+ "eval_rouge2": 0.36182153145062224,
1544
+ "eval_rougeL": 0.5317061134915853,
1545
+ "eval_rougeLsum": 0.6413066299251913,
1546
+ "eval_runtime": 15.0256,
1547
+ "eval_samples_per_second": 0.666,
1548
+ "eval_steps_per_second": 0.333,
1549
+ "step": 15400
1550
+ },
1551
+ {
1552
+ "epoch": 1.78,
1553
+ "grad_norm": 0.3436201512813568,
1554
+ "learning_rate": 0.00011115731905318027,
1555
+ "loss": 1.539,
1556
+ "step": 15600
1557
+ },
1558
+ {
1559
+ "epoch": 1.78,
1560
+ "eval_bertscore": 0.7335551977157593,
1561
+ "eval_loss": 1.7254730463027954,
1562
+ "eval_rouge1": 0.6388518781767971,
1563
+ "eval_rouge2": 0.3501853846588857,
1564
+ "eval_rougeL": 0.5196828245794569,
1565
+ "eval_rougeLsum": 0.629333993884722,
1566
+ "eval_runtime": 15.2595,
1567
+ "eval_samples_per_second": 0.655,
1568
+ "eval_steps_per_second": 0.328,
1569
+ "step": 15600
1570
+ },
1571
+ {
1572
+ "epoch": 1.8,
1573
+ "grad_norm": 0.3428190350532532,
1574
+ "learning_rate": 0.00011001794513914605,
1575
+ "loss": 1.5273,
1576
+ "step": 15800
1577
+ },
1578
+ {
1579
+ "epoch": 1.8,
1580
+ "eval_bertscore": 0.7331770658493042,
1581
+ "eval_loss": 1.7286018133163452,
1582
+ "eval_rouge1": 0.6581941047310954,
1583
+ "eval_rouge2": 0.36277983926897583,
1584
+ "eval_rougeL": 0.5336464680120501,
1585
+ "eval_rougeLsum": 0.6489239720278894,
1586
+ "eval_runtime": 14.8252,
1587
+ "eval_samples_per_second": 0.675,
1588
+ "eval_steps_per_second": 0.337,
1589
+ "step": 15800
1590
+ },
1591
+ {
1592
+ "epoch": 1.82,
1593
+ "grad_norm": 0.363164484500885,
1594
+ "learning_rate": 0.0001088785712251118,
1595
+ "loss": 1.5445,
1596
+ "step": 16000
1597
+ },
1598
+ {
1599
+ "epoch": 1.82,
1600
+ "eval_bertscore": 0.7377282977104187,
1601
+ "eval_loss": 1.7363064289093018,
1602
+ "eval_rouge1": 0.6547011011872876,
1603
+ "eval_rouge2": 0.3553220826957326,
1604
+ "eval_rougeL": 0.5256073814411315,
1605
+ "eval_rougeLsum": 0.6420095316923398,
1606
+ "eval_runtime": 14.8599,
1607
+ "eval_samples_per_second": 0.673,
1608
+ "eval_steps_per_second": 0.336,
1609
+ "step": 16000
1610
+ },
1611
+ {
1612
+ "epoch": 1.85,
1613
+ "grad_norm": 0.3098333775997162,
1614
+ "learning_rate": 0.00010773919731107757,
1615
+ "loss": 1.5319,
1616
+ "step": 16200
1617
+ },
1618
+ {
1619
+ "epoch": 1.85,
1620
+ "eval_bertscore": 0.7324053645133972,
1621
+ "eval_loss": 1.7284066677093506,
1622
+ "eval_rouge1": 0.6477379941950916,
1623
+ "eval_rouge2": 0.3535918140554809,
1624
+ "eval_rougeL": 0.5226838544730126,
1625
+ "eval_rougeLsum": 0.6373271915355557,
1626
+ "eval_runtime": 14.9318,
1627
+ "eval_samples_per_second": 0.67,
1628
+ "eval_steps_per_second": 0.335,
1629
+ "step": 16200
1630
+ },
1631
+ {
1632
+ "epoch": 1.87,
1633
+ "grad_norm": 0.3637208938598633,
1634
+ "learning_rate": 0.00010659982339704332,
1635
+ "loss": 1.5442,
1636
+ "step": 16400
1637
+ },
1638
+ {
1639
+ "epoch": 1.87,
1640
+ "eval_bertscore": 0.7347462773323059,
1641
+ "eval_loss": 1.7252963781356812,
1642
+ "eval_rouge1": 0.6494449840449819,
1643
+ "eval_rouge2": 0.3586550050575282,
1644
+ "eval_rougeL": 0.5275675395159809,
1645
+ "eval_rougeLsum": 0.6396738714026391,
1646
+ "eval_runtime": 15.2218,
1647
+ "eval_samples_per_second": 0.657,
1648
+ "eval_steps_per_second": 0.328,
1649
+ "step": 16400
1650
+ },
1651
+ {
1652
+ "epoch": 1.89,
1653
+ "grad_norm": 0.35197457671165466,
1654
+ "learning_rate": 0.00010546044948300908,
1655
+ "loss": 1.5131,
1656
+ "step": 16600
1657
+ },
1658
+ {
1659
+ "epoch": 1.89,
1660
+ "eval_bertscore": 0.7329785227775574,
1661
+ "eval_loss": 1.7285687923431396,
1662
+ "eval_rouge1": 0.6582047811143328,
1663
+ "eval_rouge2": 0.3637700686094697,
1664
+ "eval_rougeL": 0.5355021948480279,
1665
+ "eval_rougeLsum": 0.6483245595148677,
1666
+ "eval_runtime": 14.8772,
1667
+ "eval_samples_per_second": 0.672,
1668
+ "eval_steps_per_second": 0.336,
1669
+ "step": 16600
1670
+ },
1671
+ {
1672
+ "epoch": 1.91,
1673
+ "grad_norm": 0.3406757116317749,
1674
+ "learning_rate": 0.00010432107556897486,
1675
+ "loss": 1.5394,
1676
+ "step": 16800
1677
+ },
1678
+ {
1679
+ "epoch": 1.91,
1680
+ "eval_bertscore": 0.7345961332321167,
1681
+ "eval_loss": 1.7324028015136719,
1682
+ "eval_rouge1": 0.6408293615351552,
1683
+ "eval_rouge2": 0.3520120690778129,
1684
+ "eval_rougeL": 0.5145218014745592,
1685
+ "eval_rougeLsum": 0.6297802607384266,
1686
+ "eval_runtime": 15.1044,
1687
+ "eval_samples_per_second": 0.662,
1688
+ "eval_steps_per_second": 0.331,
1689
+ "step": 16800
1690
+ },
1691
+ {
1692
+ "epoch": 1.94,
1693
+ "grad_norm": 0.3417683243751526,
1694
+ "learning_rate": 0.00010318170165494061,
1695
+ "loss": 1.526,
1696
+ "step": 17000
1697
+ },
1698
+ {
1699
+ "epoch": 1.94,
1700
+ "eval_bertscore": 0.735752522945404,
1701
+ "eval_loss": 1.7288110256195068,
1702
+ "eval_rouge1": 0.641158513352794,
1703
+ "eval_rouge2": 0.3544166440855814,
1704
+ "eval_rougeL": 0.5215201980495414,
1705
+ "eval_rougeLsum": 0.630550065494593,
1706
+ "eval_runtime": 15.0797,
1707
+ "eval_samples_per_second": 0.663,
1708
+ "eval_steps_per_second": 0.332,
1709
+ "step": 17000
1710
+ },
1711
+ {
1712
+ "epoch": 1.96,
1713
+ "grad_norm": 0.3256611227989197,
1714
+ "learning_rate": 0.00010204232774090639,
1715
+ "loss": 1.5484,
1716
+ "step": 17200
1717
+ },
1718
+ {
1719
+ "epoch": 1.96,
1720
+ "eval_bertscore": 0.7356327772140503,
1721
+ "eval_loss": 1.7305186986923218,
1722
+ "eval_rouge1": 0.6400269226515611,
1723
+ "eval_rouge2": 0.3502884634173268,
1724
+ "eval_rougeL": 0.517312321281175,
1725
+ "eval_rougeLsum": 0.6284556997614409,
1726
+ "eval_runtime": 15.4097,
1727
+ "eval_samples_per_second": 0.649,
1728
+ "eval_steps_per_second": 0.324,
1729
+ "step": 17200
1730
+ },
1731
+ {
1732
+ "epoch": 1.98,
1733
+ "grad_norm": 0.4035187363624573,
1734
+ "learning_rate": 0.00010090295382687213,
1735
+ "loss": 1.5261,
1736
+ "step": 17400
1737
+ },
1738
+ {
1739
+ "epoch": 1.98,
1740
+ "eval_bertscore": 0.7339992523193359,
1741
+ "eval_loss": 1.7282793521881104,
1742
+ "eval_rouge1": 0.6335770390416183,
1743
+ "eval_rouge2": 0.34592404578075897,
1744
+ "eval_rougeL": 0.5109045259792113,
1745
+ "eval_rougeLsum": 0.6218413683710426,
1746
+ "eval_runtime": 15.1959,
1747
+ "eval_samples_per_second": 0.658,
1748
+ "eval_steps_per_second": 0.329,
1749
+ "step": 17400
1750
+ },
1751
+ {
1752
+ "epoch": 2.0,
1753
+ "grad_norm": 0.34987062215805054,
1754
+ "learning_rate": 9.97635799128379e-05,
1755
+ "loss": 1.5199,
1756
+ "step": 17600
1757
+ },
1758
+ {
1759
+ "epoch": 2.0,
1760
+ "eval_bertscore": 0.7326329946517944,
1761
+ "eval_loss": 1.7544715404510498,
1762
+ "eval_rouge1": 0.6451558045750205,
1763
+ "eval_rouge2": 0.35565806935653943,
1764
+ "eval_rougeL": 0.5217034865840529,
1765
+ "eval_rougeLsum": 0.6329869715356753,
1766
+ "eval_runtime": 15.0351,
1767
+ "eval_samples_per_second": 0.665,
1768
+ "eval_steps_per_second": 0.333,
1769
+ "step": 17600
1770
+ },
1771
+ {
1772
+ "epoch": 2.03,
1773
+ "grad_norm": 0.37184038758277893,
1774
+ "learning_rate": 9.862420599880366e-05,
1775
+ "loss": 1.41,
1776
+ "step": 17800
1777
+ },
1778
+ {
1779
+ "epoch": 2.03,
1780
+ "eval_bertscore": 0.7315141558647156,
1781
+ "eval_loss": 1.7585878372192383,
1782
+ "eval_rouge1": 0.6469319193583706,
1783
+ "eval_rouge2": 0.3514447211469598,
1784
+ "eval_rougeL": 0.524755857688278,
1785
+ "eval_rougeLsum": 0.6350164781858667,
1786
+ "eval_runtime": 14.9583,
1787
+ "eval_samples_per_second": 0.669,
1788
+ "eval_steps_per_second": 0.334,
1789
+ "step": 17800
1790
+ },
1791
+ {
1792
+ "epoch": 2.05,
1793
+ "grad_norm": 0.3812776803970337,
1794
+ "learning_rate": 9.748483208476943e-05,
1795
+ "loss": 1.4132,
1796
+ "step": 18000
1797
+ },
1798
+ {
1799
+ "epoch": 2.05,
1800
+ "eval_bertscore": 0.7335561513900757,
1801
+ "eval_loss": 1.764611840248108,
1802
+ "eval_rouge1": 0.6381916780473581,
1803
+ "eval_rouge2": 0.3482510604092539,
1804
+ "eval_rougeL": 0.5162105225823392,
1805
+ "eval_rougeLsum": 0.627150245441782,
1806
+ "eval_runtime": 15.8515,
1807
+ "eval_samples_per_second": 0.631,
1808
+ "eval_steps_per_second": 0.315,
1809
+ "step": 18000
1810
+ },
1811
+ {
1812
+ "epoch": 2.07,
1813
+ "grad_norm": 0.45525220036506653,
1814
+ "learning_rate": 9.634545817073518e-05,
1815
+ "loss": 1.4,
1816
+ "step": 18200
1817
+ },
1818
+ {
1819
+ "epoch": 2.07,
1820
+ "eval_bertscore": 0.73627769947052,
1821
+ "eval_loss": 1.7585163116455078,
1822
+ "eval_rouge1": 0.6670097658027134,
1823
+ "eval_rouge2": 0.3658295359911405,
1824
+ "eval_rougeL": 0.5429667657900548,
1825
+ "eval_rougeLsum": 0.6543501745791419,
1826
+ "eval_runtime": 15.0301,
1827
+ "eval_samples_per_second": 0.665,
1828
+ "eval_steps_per_second": 0.333,
1829
+ "step": 18200
1830
+ },
1831
+ {
1832
+ "epoch": 2.1,
1833
+ "grad_norm": 0.37322184443473816,
1834
+ "learning_rate": 9.520608425670095e-05,
1835
+ "loss": 1.4293,
1836
+ "step": 18400
1837
+ },
1838
+ {
1839
+ "epoch": 2.1,
1840
+ "eval_bertscore": 0.730435848236084,
1841
+ "eval_loss": 1.764052391052246,
1842
+ "eval_rouge1": 0.6640215078213034,
1843
+ "eval_rouge2": 0.3625932287322054,
1844
+ "eval_rougeL": 0.5379978391335138,
1845
+ "eval_rougeLsum": 0.6542054656293199,
1846
+ "eval_runtime": 15.0762,
1847
+ "eval_samples_per_second": 0.663,
1848
+ "eval_steps_per_second": 0.332,
1849
+ "step": 18400
1850
+ },
1851
+ {
1852
+ "epoch": 2.12,
1853
+ "grad_norm": 0.4260891079902649,
1854
+ "learning_rate": 9.40667103426667e-05,
1855
+ "loss": 1.4077,
1856
+ "step": 18600
1857
+ },
1858
+ {
1859
+ "epoch": 2.12,
1860
+ "eval_bertscore": 0.7309869527816772,
1861
+ "eval_loss": 1.762108564376831,
1862
+ "eval_rouge1": 0.6571171081737958,
1863
+ "eval_rouge2": 0.35780421333141865,
1864
+ "eval_rougeL": 0.5320129270967632,
1865
+ "eval_rougeLsum": 0.64587787409523,
1866
+ "eval_runtime": 14.9004,
1867
+ "eval_samples_per_second": 0.671,
1868
+ "eval_steps_per_second": 0.336,
1869
+ "step": 18600
1870
+ },
1871
+ {
1872
+ "epoch": 2.14,
1873
+ "grad_norm": 0.39479926228523254,
1874
+ "learning_rate": 9.292733642863247e-05,
1875
+ "loss": 1.4165,
1876
+ "step": 18800
1877
+ },
1878
+ {
1879
+ "epoch": 2.14,
1880
+ "eval_bertscore": 0.7324444651603699,
1881
+ "eval_loss": 1.7607113122940063,
1882
+ "eval_rouge1": 0.6628398862884018,
1883
+ "eval_rouge2": 0.3627259806721216,
1884
+ "eval_rougeL": 0.5366106483832656,
1885
+ "eval_rougeLsum": 0.6528364858807157,
1886
+ "eval_runtime": 15.5766,
1887
+ "eval_samples_per_second": 0.642,
1888
+ "eval_steps_per_second": 0.321,
1889
+ "step": 18800
1890
+ },
1891
+ {
1892
+ "epoch": 2.16,
1893
+ "grad_norm": 0.39267703890800476,
1894
+ "learning_rate": 9.178796251459824e-05,
1895
+ "loss": 1.4123,
1896
+ "step": 19000
1897
+ },
1898
+ {
1899
+ "epoch": 2.16,
1900
+ "eval_bertscore": 0.7298994064331055,
1901
+ "eval_loss": 1.7668545246124268,
1902
+ "eval_rouge1": 0.6490850022857569,
1903
+ "eval_rouge2": 0.3532323419511264,
1904
+ "eval_rougeL": 0.5212823000193295,
1905
+ "eval_rougeLsum": 0.636442724466695,
1906
+ "eval_runtime": 14.9094,
1907
+ "eval_samples_per_second": 0.671,
1908
+ "eval_steps_per_second": 0.335,
1909
+ "step": 19000
1910
+ },
1911
+ {
1912
+ "epoch": 2.19,
1913
+ "grad_norm": 0.38221287727355957,
1914
+ "learning_rate": 9.0648588600564e-05,
1915
+ "loss": 1.401,
1916
+ "step": 19200
1917
+ },
1918
+ {
1919
+ "epoch": 2.19,
1920
+ "eval_bertscore": 0.7316875457763672,
1921
+ "eval_loss": 1.764147400856018,
1922
+ "eval_rouge1": 0.6490326710625849,
1923
+ "eval_rouge2": 0.3510351037900723,
1924
+ "eval_rougeL": 0.5239165028795836,
1925
+ "eval_rougeLsum": 0.6373687316421427,
1926
+ "eval_runtime": 15.1192,
1927
+ "eval_samples_per_second": 0.661,
1928
+ "eval_steps_per_second": 0.331,
1929
+ "step": 19200
1930
+ },
1931
+ {
1932
+ "epoch": 2.21,
1933
+ "grad_norm": 0.3653150200843811,
1934
+ "learning_rate": 8.950921468652976e-05,
1935
+ "loss": 1.4109,
1936
+ "step": 19400
1937
+ },
1938
+ {
1939
+ "epoch": 2.21,
1940
+ "eval_bertscore": 0.7348155975341797,
1941
+ "eval_loss": 1.7640550136566162,
1942
+ "eval_rouge1": 0.6462152873276823,
1943
+ "eval_rouge2": 0.3483599145461069,
1944
+ "eval_rougeL": 0.5193372430687719,
1945
+ "eval_rougeLsum": 0.6334254357511564,
1946
+ "eval_runtime": 14.9291,
1947
+ "eval_samples_per_second": 0.67,
1948
+ "eval_steps_per_second": 0.335,
1949
+ "step": 19400
1950
+ },
1951
+ {
1952
+ "epoch": 2.23,
1953
+ "grad_norm": 0.38049009442329407,
1954
+ "learning_rate": 8.836984077249551e-05,
1955
+ "loss": 1.4189,
1956
+ "step": 19600
1957
+ },
1958
+ {
1959
+ "epoch": 2.23,
1960
+ "eval_bertscore": 0.7357938885688782,
1961
+ "eval_loss": 1.7696326971054077,
1962
+ "eval_rouge1": 0.6377276221057538,
1963
+ "eval_rouge2": 0.3455397190390045,
1964
+ "eval_rougeL": 0.5118069428064842,
1965
+ "eval_rougeLsum": 0.6264501633078481,
1966
+ "eval_runtime": 14.8653,
1967
+ "eval_samples_per_second": 0.673,
1968
+ "eval_steps_per_second": 0.336,
1969
+ "step": 19600
1970
+ },
1971
+ {
1972
+ "epoch": 2.26,
1973
+ "grad_norm": 0.42111098766326904,
1974
+ "learning_rate": 8.723046685846128e-05,
1975
+ "loss": 1.4152,
1976
+ "step": 19800
1977
+ },
1978
+ {
1979
+ "epoch": 2.26,
1980
+ "eval_bertscore": 0.7339056134223938,
1981
+ "eval_loss": 1.7658218145370483,
1982
+ "eval_rouge1": 0.6494820372695989,
1983
+ "eval_rouge2": 0.34691658128805236,
1984
+ "eval_rougeL": 0.5193228965163086,
1985
+ "eval_rougeLsum": 0.6365347065687565,
1986
+ "eval_runtime": 15.3562,
1987
+ "eval_samples_per_second": 0.651,
1988
+ "eval_steps_per_second": 0.326,
1989
+ "step": 19800
1990
+ },
1991
+ {
1992
+ "epoch": 2.28,
1993
+ "grad_norm": 0.4452258050441742,
1994
+ "learning_rate": 8.609109294442704e-05,
1995
+ "loss": 1.4101,
1996
+ "step": 20000
1997
+ },
1998
+ {
1999
+ "epoch": 2.28,
2000
+ "eval_bertscore": 0.7296434640884399,
2001
+ "eval_loss": 1.7714240550994873,
2002
+ "eval_rouge1": 0.6565600824405751,
2003
+ "eval_rouge2": 0.3533618655201594,
2004
+ "eval_rougeL": 0.5263318202066467,
2005
+ "eval_rougeLsum": 0.6444964824298407,
2006
+ "eval_runtime": 14.8578,
2007
+ "eval_samples_per_second": 0.673,
2008
+ "eval_steps_per_second": 0.337,
2009
+ "step": 20000
2010
+ }
2011
+ ],
2012
+ "logging_steps": 200,
2013
+ "max_steps": 35112,
2014
+ "num_input_tokens_seen": 0,
2015
+ "num_train_epochs": 4,
2016
+ "save_steps": 800,
2017
+ "total_flos": 2.0270434657179034e+18,
2018
+ "train_batch_size": 2,
2019
+ "trial_name": null,
2020
+ "trial_params": null
2021
+ }
checkpoint-20000/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d576743d4294cfbcae212243377437f73cabbcded2df9da7f73e6e39ecb38f56
3
+ size 5048
checkpoint-20800/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: peft
3
+ base_model: unsloth/gemma-2b-bnb-4bit
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.10.0
checkpoint-20800/adapter_config.json ADDED
@@ -0,0 +1,34 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "unsloth/gemma-2b-bnb-4bit",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 32,
14
+ "lora_dropout": 0,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 64,
20
+ "rank_pattern": {},
21
+ "revision": "unsloth",
22
+ "target_modules": [
23
+ "v_proj",
24
+ "up_proj",
25
+ "gate_proj",
26
+ "o_proj",
27
+ "k_proj",
28
+ "down_proj",
29
+ "q_proj"
30
+ ],
31
+ "task_type": "CAUSAL_LM",
32
+ "use_dora": false,
33
+ "use_rslora": false
34
+ }
checkpoint-20800/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:8bbe4df1701bf265adab036c3e96cb82f9cb29bffaf953f7cc1cc5f43da0a96a
3
+ size 313820248
checkpoint-20800/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:769c9d116d716759c38c18535106ad97215ee71bcb7213d14aa01a6e2eeb4af3
3
+ size 14244
checkpoint-20800/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c63a677b50085086e66ea55fbe01bc8715f3747ab6b695c5ef7d013aa1811797
3
+ size 1064
checkpoint-20800/special_tokens_map.json ADDED
@@ -0,0 +1,34 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "additional_special_tokens": [
3
+ "<start_of_turn>",
4
+ "<end_of_turn>"
5
+ ],
6
+ "bos_token": {
7
+ "content": "<bos>",
8
+ "lstrip": false,
9
+ "normalized": false,
10
+ "rstrip": false,
11
+ "single_word": false
12
+ },
13
+ "eos_token": {
14
+ "content": "<eos>",
15
+ "lstrip": false,
16
+ "normalized": false,
17
+ "rstrip": false,
18
+ "single_word": false
19
+ },
20
+ "pad_token": {
21
+ "content": "<pad>",
22
+ "lstrip": false,
23
+ "normalized": false,
24
+ "rstrip": false,
25
+ "single_word": false
26
+ },
27
+ "unk_token": {
28
+ "content": "<unk>",
29
+ "lstrip": false,
30
+ "normalized": false,
31
+ "rstrip": false,
32
+ "single_word": false
33
+ }
34
+ }
checkpoint-20800/tokenizer.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:05e97791a5e007260de1db7e1692e53150e08cea481e2bf25435553380c147ee
3
+ size 17477929
checkpoint-20800/tokenizer.model ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:61a7b147390c64585d6c3543dd6fc636906c9af3865a5548f27f31aee1d4c8e2
3
+ size 4241003
checkpoint-20800/tokenizer_config.json ADDED
@@ -0,0 +1,71 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_bos_token": true,
3
+ "add_eos_token": false,
4
+ "added_tokens_decoder": {
5
+ "0": {
6
+ "content": "<pad>",
7
+ "lstrip": false,
8
+ "normalized": false,
9
+ "rstrip": false,
10
+ "single_word": false,
11
+ "special": true
12
+ },
13
+ "1": {
14
+ "content": "<eos>",
15
+ "lstrip": false,
16
+ "normalized": false,
17
+ "rstrip": false,
18
+ "single_word": false,
19
+ "special": true
20
+ },
21
+ "2": {
22
+ "content": "<bos>",
23
+ "lstrip": false,
24
+ "normalized": false,
25
+ "rstrip": false,
26
+ "single_word": false,
27
+ "special": true
28
+ },
29
+ "3": {
30
+ "content": "<unk>",
31
+ "lstrip": false,
32
+ "normalized": false,
33
+ "rstrip": false,
34
+ "single_word": false,
35
+ "special": true
36
+ },
37
+ "106": {
38
+ "content": "<start_of_turn>",
39
+ "lstrip": false,
40
+ "normalized": false,
41
+ "rstrip": false,
42
+ "single_word": false,
43
+ "special": true
44
+ },
45
+ "107": {
46
+ "content": "<end_of_turn>",
47
+ "lstrip": false,
48
+ "normalized": false,
49
+ "rstrip": false,
50
+ "single_word": false,
51
+ "special": true
52
+ }
53
+ },
54
+ "additional_special_tokens": [
55
+ "<start_of_turn>",
56
+ "<end_of_turn>"
57
+ ],
58
+ "bos_token": "<bos>",
59
+ "chat_template": "{{ bos_token }}{% if messages[0]['role'] == 'system' %}{{ raise_exception('System role not supported') }}{% endif %}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if (message['role'] == 'assistant') %}{% set role = 'model' %}{% else %}{% set role = message['role'] %}{% endif %}{{ '<start_of_turn>' + role + '\n' + message['content'] | trim + '<end_of_turn>\n' }}{% endfor %}{% if add_generation_prompt %}{{'<start_of_turn>model\n'}}{% endif %}",
60
+ "clean_up_tokenization_spaces": false,
61
+ "eos_token": "<eos>",
62
+ "legacy": null,
63
+ "model_max_length": 8192,
64
+ "pad_token": "<pad>",
65
+ "padding_side": "right",
66
+ "sp_model_kwargs": {},
67
+ "spaces_between_special_tokens": false,
68
+ "tokenizer_class": "GemmaTokenizer",
69
+ "unk_token": "<unk>",
70
+ "use_default_system_prompt": false
71
+ }
checkpoint-20800/trainer_state.json ADDED
@@ -0,0 +1,2101 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": null,
3
+ "best_model_checkpoint": null,
4
+ "epoch": 2.369425300449963,
5
+ "eval_steps": 200,
6
+ "global_step": 20800,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.02,
13
+ "grad_norm": 0.1643640249967575,
14
+ "learning_rate": 0.0001988891104338166,
15
+ "loss": 1.7673,
16
+ "step": 200
17
+ },
18
+ {
19
+ "epoch": 0.02,
20
+ "eval_bertscore": 0.7312520742416382,
21
+ "eval_loss": 1.7944419384002686,
22
+ "eval_rouge1": 0.645726048132668,
23
+ "eval_rouge2": 0.342840307585653,
24
+ "eval_rougeL": 0.5174784271125388,
25
+ "eval_rougeLsum": 0.6359911842715976,
26
+ "eval_runtime": 67.7968,
27
+ "eval_samples_per_second": 0.147,
28
+ "eval_steps_per_second": 0.074,
29
+ "step": 200
30
+ },
31
+ {
32
+ "epoch": 0.05,
33
+ "grad_norm": 0.17238478362560272,
34
+ "learning_rate": 0.00019774973651978238,
35
+ "loss": 1.6985,
36
+ "step": 400
37
+ },
38
+ {
39
+ "epoch": 0.05,
40
+ "eval_bertscore": 0.733666718006134,
41
+ "eval_loss": 1.7791178226470947,
42
+ "eval_rouge1": 0.6540909153028596,
43
+ "eval_rouge2": 0.3548819059818129,
44
+ "eval_rougeL": 0.527257232694246,
45
+ "eval_rougeLsum": 0.6442799950994005,
46
+ "eval_runtime": 15.1267,
47
+ "eval_samples_per_second": 0.661,
48
+ "eval_steps_per_second": 0.331,
49
+ "step": 400
50
+ },
51
+ {
52
+ "epoch": 0.07,
53
+ "grad_norm": 0.19368696212768555,
54
+ "learning_rate": 0.00019661036260574814,
55
+ "loss": 1.6962,
56
+ "step": 600
57
+ },
58
+ {
59
+ "epoch": 0.07,
60
+ "eval_bertscore": 0.7339462041854858,
61
+ "eval_loss": 1.7609882354736328,
62
+ "eval_rouge1": 0.6384337329686338,
63
+ "eval_rouge2": 0.3415514270662107,
64
+ "eval_rougeL": 0.51206080148464,
65
+ "eval_rougeLsum": 0.6261968614666548,
66
+ "eval_runtime": 15.2068,
67
+ "eval_samples_per_second": 0.658,
68
+ "eval_steps_per_second": 0.329,
69
+ "step": 600
70
+ },
71
+ {
72
+ "epoch": 0.09,
73
+ "grad_norm": 0.18629203736782074,
74
+ "learning_rate": 0.00019547098869171392,
75
+ "loss": 1.6825,
76
+ "step": 800
77
+ },
78
+ {
79
+ "epoch": 0.09,
80
+ "eval_bertscore": 0.7363594174385071,
81
+ "eval_loss": 1.7610784769058228,
82
+ "eval_rouge1": 0.6461624591922237,
83
+ "eval_rouge2": 0.3477371388439609,
84
+ "eval_rougeL": 0.5187429174752844,
85
+ "eval_rougeLsum": 0.6361089823008282,
86
+ "eval_runtime": 15.173,
87
+ "eval_samples_per_second": 0.659,
88
+ "eval_steps_per_second": 0.33,
89
+ "step": 800
90
+ },
91
+ {
92
+ "epoch": 0.11,
93
+ "grad_norm": 0.1799013316631317,
94
+ "learning_rate": 0.00019433161477767967,
95
+ "loss": 1.6848,
96
+ "step": 1000
97
+ },
98
+ {
99
+ "epoch": 0.11,
100
+ "eval_bertscore": 0.7334067225456238,
101
+ "eval_loss": 1.7576347589492798,
102
+ "eval_rouge1": 0.6345119236349537,
103
+ "eval_rouge2": 0.3422519149071803,
104
+ "eval_rougeL": 0.5111983101326238,
105
+ "eval_rougeLsum": 0.6244653120436832,
106
+ "eval_runtime": 15.2847,
107
+ "eval_samples_per_second": 0.654,
108
+ "eval_steps_per_second": 0.327,
109
+ "step": 1000
110
+ },
111
+ {
112
+ "epoch": 0.14,
113
+ "grad_norm": 0.22036150097846985,
114
+ "learning_rate": 0.00019319224086364545,
115
+ "loss": 1.6714,
116
+ "step": 1200
117
+ },
118
+ {
119
+ "epoch": 0.14,
120
+ "eval_bertscore": 0.7323788404464722,
121
+ "eval_loss": 1.7521806955337524,
122
+ "eval_rouge1": 0.6452540184557478,
123
+ "eval_rouge2": 0.3465145726476423,
124
+ "eval_rougeL": 0.516711757588783,
125
+ "eval_rougeLsum": 0.6341049885677059,
126
+ "eval_runtime": 15.1247,
127
+ "eval_samples_per_second": 0.661,
128
+ "eval_steps_per_second": 0.331,
129
+ "step": 1200
130
+ },
131
+ {
132
+ "epoch": 0.16,
133
+ "grad_norm": 0.21381086111068726,
134
+ "learning_rate": 0.0001920528669496112,
135
+ "loss": 1.6669,
136
+ "step": 1400
137
+ },
138
+ {
139
+ "epoch": 0.16,
140
+ "eval_bertscore": 0.7313202619552612,
141
+ "eval_loss": 1.7520482540130615,
142
+ "eval_rouge1": 0.6397526546254797,
143
+ "eval_rouge2": 0.3452671288110514,
144
+ "eval_rougeL": 0.5176580626678706,
145
+ "eval_rougeLsum": 0.6296746647539768,
146
+ "eval_runtime": 15.183,
147
+ "eval_samples_per_second": 0.659,
148
+ "eval_steps_per_second": 0.329,
149
+ "step": 1400
150
+ },
151
+ {
152
+ "epoch": 0.18,
153
+ "grad_norm": 0.20332874357700348,
154
+ "learning_rate": 0.00019091349303557696,
155
+ "loss": 1.671,
156
+ "step": 1600
157
+ },
158
+ {
159
+ "epoch": 0.18,
160
+ "eval_bertscore": 0.7349230647087097,
161
+ "eval_loss": 1.7473630905151367,
162
+ "eval_rouge1": 0.637439872504459,
163
+ "eval_rouge2": 0.34307164454056094,
164
+ "eval_rougeL": 0.5129717676228565,
165
+ "eval_rougeLsum": 0.6272190896182391,
166
+ "eval_runtime": 15.5672,
167
+ "eval_samples_per_second": 0.642,
168
+ "eval_steps_per_second": 0.321,
169
+ "step": 1600
170
+ },
171
+ {
172
+ "epoch": 0.21,
173
+ "grad_norm": 0.2025599479675293,
174
+ "learning_rate": 0.00018977411912154274,
175
+ "loss": 1.6721,
176
+ "step": 1800
177
+ },
178
+ {
179
+ "epoch": 0.21,
180
+ "eval_bertscore": 0.7357184290885925,
181
+ "eval_loss": 1.7516342401504517,
182
+ "eval_rouge1": 0.6387615819926658,
183
+ "eval_rouge2": 0.34366787517105574,
184
+ "eval_rougeL": 0.5129026911770751,
185
+ "eval_rougeLsum": 0.6289314118258257,
186
+ "eval_runtime": 15.9574,
187
+ "eval_samples_per_second": 0.627,
188
+ "eval_steps_per_second": 0.313,
189
+ "step": 1800
190
+ },
191
+ {
192
+ "epoch": 0.23,
193
+ "grad_norm": 0.20457112789154053,
194
+ "learning_rate": 0.0001886347452075085,
195
+ "loss": 1.671,
196
+ "step": 2000
197
+ },
198
+ {
199
+ "epoch": 0.23,
200
+ "eval_bertscore": 0.733718752861023,
201
+ "eval_loss": 1.7501707077026367,
202
+ "eval_rouge1": 0.6346207681220664,
203
+ "eval_rouge2": 0.33748369437614106,
204
+ "eval_rougeL": 0.5085159047705141,
205
+ "eval_rougeLsum": 0.6239953154441167,
206
+ "eval_runtime": 15.0863,
207
+ "eval_samples_per_second": 0.663,
208
+ "eval_steps_per_second": 0.331,
209
+ "step": 2000
210
+ },
211
+ {
212
+ "epoch": 0.25,
213
+ "grad_norm": 0.22552740573883057,
214
+ "learning_rate": 0.00018749537129347424,
215
+ "loss": 1.6496,
216
+ "step": 2200
217
+ },
218
+ {
219
+ "epoch": 0.25,
220
+ "eval_bertscore": 0.7368552684783936,
221
+ "eval_loss": 1.7437107563018799,
222
+ "eval_rouge1": 0.6490756387878311,
223
+ "eval_rouge2": 0.3448817738175175,
224
+ "eval_rougeL": 0.5235187045706321,
225
+ "eval_rougeLsum": 0.6377780857890332,
226
+ "eval_runtime": 15.07,
227
+ "eval_samples_per_second": 0.664,
228
+ "eval_steps_per_second": 0.332,
229
+ "step": 2200
230
+ },
231
+ {
232
+ "epoch": 0.27,
233
+ "grad_norm": 0.22573673725128174,
234
+ "learning_rate": 0.00018635599737944,
235
+ "loss": 1.6629,
236
+ "step": 2400
237
+ },
238
+ {
239
+ "epoch": 0.27,
240
+ "eval_bertscore": 0.7314499616622925,
241
+ "eval_loss": 1.7462828159332275,
242
+ "eval_rouge1": 0.6511482369678803,
243
+ "eval_rouge2": 0.34632544827771805,
244
+ "eval_rougeL": 0.5212417191003778,
245
+ "eval_rougeLsum": 0.6415391907940229,
246
+ "eval_runtime": 15.2078,
247
+ "eval_samples_per_second": 0.658,
248
+ "eval_steps_per_second": 0.329,
249
+ "step": 2400
250
+ },
251
+ {
252
+ "epoch": 0.3,
253
+ "grad_norm": 0.26426687836647034,
254
+ "learning_rate": 0.00018521662346540575,
255
+ "loss": 1.6644,
256
+ "step": 2600
257
+ },
258
+ {
259
+ "epoch": 0.3,
260
+ "eval_bertscore": 0.7363359928131104,
261
+ "eval_loss": 1.7505037784576416,
262
+ "eval_rouge1": 0.6498296552335481,
263
+ "eval_rouge2": 0.34873833589761183,
264
+ "eval_rougeL": 0.5194028620820592,
265
+ "eval_rougeLsum": 0.6404603087578984,
266
+ "eval_runtime": 14.8403,
267
+ "eval_samples_per_second": 0.674,
268
+ "eval_steps_per_second": 0.337,
269
+ "step": 2600
270
+ },
271
+ {
272
+ "epoch": 0.32,
273
+ "grad_norm": 0.20142091810703278,
274
+ "learning_rate": 0.00018407724955137153,
275
+ "loss": 1.6535,
276
+ "step": 2800
277
+ },
278
+ {
279
+ "epoch": 0.32,
280
+ "eval_bertscore": 0.7304679155349731,
281
+ "eval_loss": 1.7511039972305298,
282
+ "eval_rouge1": 0.6475130585388738,
283
+ "eval_rouge2": 0.34648331046897884,
284
+ "eval_rougeL": 0.5218042284020985,
285
+ "eval_rougeLsum": 0.6382749834402862,
286
+ "eval_runtime": 15.0162,
287
+ "eval_samples_per_second": 0.666,
288
+ "eval_steps_per_second": 0.333,
289
+ "step": 2800
290
+ },
291
+ {
292
+ "epoch": 0.34,
293
+ "grad_norm": 0.23283220827579498,
294
+ "learning_rate": 0.00018293787563733728,
295
+ "loss": 1.6477,
296
+ "step": 3000
297
+ },
298
+ {
299
+ "epoch": 0.34,
300
+ "eval_bertscore": 0.7327049374580383,
301
+ "eval_loss": 1.7461665868759155,
302
+ "eval_rouge1": 0.6309349586871908,
303
+ "eval_rouge2": 0.3387882478990309,
304
+ "eval_rougeL": 0.5042059192403674,
305
+ "eval_rougeLsum": 0.6210432469674847,
306
+ "eval_runtime": 15.463,
307
+ "eval_samples_per_second": 0.647,
308
+ "eval_steps_per_second": 0.323,
309
+ "step": 3000
310
+ },
311
+ {
312
+ "epoch": 0.36,
313
+ "grad_norm": 0.21316750347614288,
314
+ "learning_rate": 0.00018179850172330306,
315
+ "loss": 1.6614,
316
+ "step": 3200
317
+ },
318
+ {
319
+ "epoch": 0.36,
320
+ "eval_bertscore": 0.7314620018005371,
321
+ "eval_loss": 1.7468239068984985,
322
+ "eval_rouge1": 0.6480904534152265,
323
+ "eval_rouge2": 0.3479530168963481,
324
+ "eval_rougeL": 0.5193148273848067,
325
+ "eval_rougeLsum": 0.6366010767207634,
326
+ "eval_runtime": 15.0381,
327
+ "eval_samples_per_second": 0.665,
328
+ "eval_steps_per_second": 0.332,
329
+ "step": 3200
330
+ },
331
+ {
332
+ "epoch": 0.39,
333
+ "grad_norm": 0.26080408692359924,
334
+ "learning_rate": 0.00018065912780926882,
335
+ "loss": 1.6591,
336
+ "step": 3400
337
+ },
338
+ {
339
+ "epoch": 0.39,
340
+ "eval_bertscore": 0.7327477335929871,
341
+ "eval_loss": 1.7442594766616821,
342
+ "eval_rouge1": 0.6424613378037144,
343
+ "eval_rouge2": 0.34731770322974903,
344
+ "eval_rougeL": 0.5160705879794565,
345
+ "eval_rougeLsum": 0.6327006420281607,
346
+ "eval_runtime": 15.5373,
347
+ "eval_samples_per_second": 0.644,
348
+ "eval_steps_per_second": 0.322,
349
+ "step": 3400
350
+ },
351
+ {
352
+ "epoch": 0.41,
353
+ "grad_norm": 0.23274216055870056,
354
+ "learning_rate": 0.0001795197538952346,
355
+ "loss": 1.6613,
356
+ "step": 3600
357
+ },
358
+ {
359
+ "epoch": 0.41,
360
+ "eval_bertscore": 0.736956000328064,
361
+ "eval_loss": 1.7429373264312744,
362
+ "eval_rouge1": 0.6514574160666677,
363
+ "eval_rouge2": 0.3556199242231646,
364
+ "eval_rougeL": 0.5249726237675663,
365
+ "eval_rougeLsum": 0.6406261097623661,
366
+ "eval_runtime": 14.9415,
367
+ "eval_samples_per_second": 0.669,
368
+ "eval_steps_per_second": 0.335,
369
+ "step": 3600
370
+ },
371
+ {
372
+ "epoch": 0.43,
373
+ "grad_norm": 0.23616766929626465,
374
+ "learning_rate": 0.00017838037998120035,
375
+ "loss": 1.6479,
376
+ "step": 3800
377
+ },
378
+ {
379
+ "epoch": 0.43,
380
+ "eval_bertscore": 0.7349627614021301,
381
+ "eval_loss": 1.7420669794082642,
382
+ "eval_rouge1": 0.655851684949526,
383
+ "eval_rouge2": 0.35254590691865084,
384
+ "eval_rougeL": 0.5248980956621441,
385
+ "eval_rougeLsum": 0.6449637270581419,
386
+ "eval_runtime": 15.4178,
387
+ "eval_samples_per_second": 0.649,
388
+ "eval_steps_per_second": 0.324,
389
+ "step": 3800
390
+ },
391
+ {
392
+ "epoch": 0.46,
393
+ "grad_norm": 0.23260319232940674,
394
+ "learning_rate": 0.0001772410060671661,
395
+ "loss": 1.6569,
396
+ "step": 4000
397
+ },
398
+ {
399
+ "epoch": 0.46,
400
+ "eval_bertscore": 0.7332885265350342,
401
+ "eval_loss": 1.7401313781738281,
402
+ "eval_rouge1": 0.6669483634140105,
403
+ "eval_rouge2": 0.35873988835161297,
404
+ "eval_rougeL": 0.5343868725007427,
405
+ "eval_rougeLsum": 0.6555353134690931,
406
+ "eval_runtime": 15.0822,
407
+ "eval_samples_per_second": 0.663,
408
+ "eval_steps_per_second": 0.332,
409
+ "step": 4000
410
+ },
411
+ {
412
+ "epoch": 0.48,
413
+ "grad_norm": 0.2366473525762558,
414
+ "learning_rate": 0.00017610163215313186,
415
+ "loss": 1.6599,
416
+ "step": 4200
417
+ },
418
+ {
419
+ "epoch": 0.48,
420
+ "eval_bertscore": 0.7335314750671387,
421
+ "eval_loss": 1.7385823726654053,
422
+ "eval_rouge1": 0.6559297063578133,
423
+ "eval_rouge2": 0.35483499789990636,
424
+ "eval_rougeL": 0.5297939800986089,
425
+ "eval_rougeLsum": 0.6454544372491222,
426
+ "eval_runtime": 15.1029,
427
+ "eval_samples_per_second": 0.662,
428
+ "eval_steps_per_second": 0.331,
429
+ "step": 4200
430
+ },
431
+ {
432
+ "epoch": 0.5,
433
+ "grad_norm": 0.20628753304481506,
434
+ "learning_rate": 0.0001749622582390976,
435
+ "loss": 1.6454,
436
+ "step": 4400
437
+ },
438
+ {
439
+ "epoch": 0.5,
440
+ "eval_bertscore": 0.7342795133590698,
441
+ "eval_loss": 1.7422058582305908,
442
+ "eval_rouge1": 0.660746519614568,
443
+ "eval_rouge2": 0.3633965895561597,
444
+ "eval_rougeL": 0.5369036980876734,
445
+ "eval_rougeLsum": 0.650338328328998,
446
+ "eval_runtime": 15.4434,
447
+ "eval_samples_per_second": 0.648,
448
+ "eval_steps_per_second": 0.324,
449
+ "step": 4400
450
+ },
451
+ {
452
+ "epoch": 0.52,
453
+ "grad_norm": 0.2239149957895279,
454
+ "learning_rate": 0.0001738228843250634,
455
+ "loss": 1.6594,
456
+ "step": 4600
457
+ },
458
+ {
459
+ "epoch": 0.52,
460
+ "eval_bertscore": 0.7313543558120728,
461
+ "eval_loss": 1.740854263305664,
462
+ "eval_rouge1": 0.6591645132619427,
463
+ "eval_rouge2": 0.35766117432431743,
464
+ "eval_rougeL": 0.532710255034635,
465
+ "eval_rougeLsum": 0.6479428185884644,
466
+ "eval_runtime": 14.9436,
467
+ "eval_samples_per_second": 0.669,
468
+ "eval_steps_per_second": 0.335,
469
+ "step": 4600
470
+ },
471
+ {
472
+ "epoch": 0.55,
473
+ "grad_norm": 0.24808338284492493,
474
+ "learning_rate": 0.00017268351041102914,
475
+ "loss": 1.6604,
476
+ "step": 4800
477
+ },
478
+ {
479
+ "epoch": 0.55,
480
+ "eval_bertscore": 0.7333321571350098,
481
+ "eval_loss": 1.7385585308074951,
482
+ "eval_rouge1": 0.6532115808232871,
483
+ "eval_rouge2": 0.35333788022501567,
484
+ "eval_rougeL": 0.5284071547874328,
485
+ "eval_rougeLsum": 0.6410472452797623,
486
+ "eval_runtime": 15.0277,
487
+ "eval_samples_per_second": 0.665,
488
+ "eval_steps_per_second": 0.333,
489
+ "step": 4800
490
+ },
491
+ {
492
+ "epoch": 0.57,
493
+ "grad_norm": 0.2555364966392517,
494
+ "learning_rate": 0.0001715441364969949,
495
+ "loss": 1.6493,
496
+ "step": 5000
497
+ },
498
+ {
499
+ "epoch": 0.57,
500
+ "eval_bertscore": 0.7318152189254761,
501
+ "eval_loss": 1.7357494831085205,
502
+ "eval_rouge1": 0.6476755890502586,
503
+ "eval_rouge2": 0.35312778275949164,
504
+ "eval_rougeL": 0.5227601228049905,
505
+ "eval_rougeLsum": 0.6371331138372852,
506
+ "eval_runtime": 14.8807,
507
+ "eval_samples_per_second": 0.672,
508
+ "eval_steps_per_second": 0.336,
509
+ "step": 5000
510
+ },
511
+ {
512
+ "epoch": 0.59,
513
+ "grad_norm": 0.21518155932426453,
514
+ "learning_rate": 0.00017040476258296068,
515
+ "loss": 1.644,
516
+ "step": 5200
517
+ },
518
+ {
519
+ "epoch": 0.59,
520
+ "eval_bertscore": 0.734805703163147,
521
+ "eval_loss": 1.74032723903656,
522
+ "eval_rouge1": 0.6476813733451636,
523
+ "eval_rouge2": 0.3509259728617576,
524
+ "eval_rougeL": 0.5221334872800274,
525
+ "eval_rougeLsum": 0.636892384667733,
526
+ "eval_runtime": 15.1271,
527
+ "eval_samples_per_second": 0.661,
528
+ "eval_steps_per_second": 0.331,
529
+ "step": 5200
530
+ },
531
+ {
532
+ "epoch": 0.62,
533
+ "grad_norm": 0.26086658239364624,
534
+ "learning_rate": 0.00016926538866892643,
535
+ "loss": 1.6449,
536
+ "step": 5400
537
+ },
538
+ {
539
+ "epoch": 0.62,
540
+ "eval_bertscore": 0.7339995503425598,
541
+ "eval_loss": 1.7338205575942993,
542
+ "eval_rouge1": 0.6416889902864902,
543
+ "eval_rouge2": 0.3479045880347737,
544
+ "eval_rougeL": 0.5160577838468976,
545
+ "eval_rougeLsum": 0.6317983411796093,
546
+ "eval_runtime": 14.9992,
547
+ "eval_samples_per_second": 0.667,
548
+ "eval_steps_per_second": 0.333,
549
+ "step": 5400
550
+ },
551
+ {
552
+ "epoch": 0.64,
553
+ "grad_norm": 0.25449469685554504,
554
+ "learning_rate": 0.0001681260147548922,
555
+ "loss": 1.6299,
556
+ "step": 5600
557
+ },
558
+ {
559
+ "epoch": 0.64,
560
+ "eval_bertscore": 0.7306328415870667,
561
+ "eval_loss": 1.7369228601455688,
562
+ "eval_rouge1": 0.6390760905985684,
563
+ "eval_rouge2": 0.3409328272828699,
564
+ "eval_rougeL": 0.5111832543685331,
565
+ "eval_rougeLsum": 0.6285753423407665,
566
+ "eval_runtime": 15.483,
567
+ "eval_samples_per_second": 0.646,
568
+ "eval_steps_per_second": 0.323,
569
+ "step": 5600
570
+ },
571
+ {
572
+ "epoch": 0.66,
573
+ "grad_norm": 0.24706102907657623,
574
+ "learning_rate": 0.00016698664084085796,
575
+ "loss": 1.6374,
576
+ "step": 5800
577
+ },
578
+ {
579
+ "epoch": 0.66,
580
+ "eval_bertscore": 0.732075572013855,
581
+ "eval_loss": 1.7343876361846924,
582
+ "eval_rouge1": 0.6378821977913272,
583
+ "eval_rouge2": 0.34619427775171585,
584
+ "eval_rougeL": 0.5120186953041237,
585
+ "eval_rougeLsum": 0.6284056323839109,
586
+ "eval_runtime": 15.7341,
587
+ "eval_samples_per_second": 0.636,
588
+ "eval_steps_per_second": 0.318,
589
+ "step": 5800
590
+ },
591
+ {
592
+ "epoch": 0.68,
593
+ "grad_norm": 0.24373260140419006,
594
+ "learning_rate": 0.00016584726692682372,
595
+ "loss": 1.6427,
596
+ "step": 6000
597
+ },
598
+ {
599
+ "epoch": 0.68,
600
+ "eval_bertscore": 0.7350374460220337,
601
+ "eval_loss": 1.729591965675354,
602
+ "eval_rouge1": 0.6516545226356616,
603
+ "eval_rouge2": 0.35485762033878543,
604
+ "eval_rougeL": 0.5249054193354852,
605
+ "eval_rougeLsum": 0.6411016821651583,
606
+ "eval_runtime": 15.5199,
607
+ "eval_samples_per_second": 0.644,
608
+ "eval_steps_per_second": 0.322,
609
+ "step": 6000
610
+ },
611
+ {
612
+ "epoch": 0.71,
613
+ "grad_norm": 0.24616578221321106,
614
+ "learning_rate": 0.0001647078930127895,
615
+ "loss": 1.6296,
616
+ "step": 6200
617
+ },
618
+ {
619
+ "epoch": 0.71,
620
+ "eval_bertscore": 0.7335461378097534,
621
+ "eval_loss": 1.7302274703979492,
622
+ "eval_rouge1": 0.6531411706717427,
623
+ "eval_rouge2": 0.35003053174601517,
624
+ "eval_rougeL": 0.5212483686089053,
625
+ "eval_rougeLsum": 0.6438454124825417,
626
+ "eval_runtime": 15.3058,
627
+ "eval_samples_per_second": 0.653,
628
+ "eval_steps_per_second": 0.327,
629
+ "step": 6200
630
+ },
631
+ {
632
+ "epoch": 0.73,
633
+ "grad_norm": 0.24500492215156555,
634
+ "learning_rate": 0.00016356851909875522,
635
+ "loss": 1.6251,
636
+ "step": 6400
637
+ },
638
+ {
639
+ "epoch": 0.73,
640
+ "eval_bertscore": 0.7347471714019775,
641
+ "eval_loss": 1.7292228937149048,
642
+ "eval_rouge1": 0.6565322485502556,
643
+ "eval_rouge2": 0.35887540291607073,
644
+ "eval_rougeL": 0.5284326132878907,
645
+ "eval_rougeLsum": 0.6469750895866724,
646
+ "eval_runtime": 14.9708,
647
+ "eval_samples_per_second": 0.668,
648
+ "eval_steps_per_second": 0.334,
649
+ "step": 6400
650
+ },
651
+ {
652
+ "epoch": 0.75,
653
+ "grad_norm": 0.26575228571891785,
654
+ "learning_rate": 0.000162429145184721,
655
+ "loss": 1.6389,
656
+ "step": 6600
657
+ },
658
+ {
659
+ "epoch": 0.75,
660
+ "eval_bertscore": 0.7319897413253784,
661
+ "eval_loss": 1.7287580966949463,
662
+ "eval_rouge1": 0.6458608801881298,
663
+ "eval_rouge2": 0.3503480901452204,
664
+ "eval_rougeL": 0.519626708150005,
665
+ "eval_rougeLsum": 0.6362405734928169,
666
+ "eval_runtime": 15.3509,
667
+ "eval_samples_per_second": 0.651,
668
+ "eval_steps_per_second": 0.326,
669
+ "step": 6600
670
+ },
671
+ {
672
+ "epoch": 0.77,
673
+ "grad_norm": 0.27144965529441833,
674
+ "learning_rate": 0.00016128977127068676,
675
+ "loss": 1.6476,
676
+ "step": 6800
677
+ },
678
+ {
679
+ "epoch": 0.77,
680
+ "eval_bertscore": 0.7392772436141968,
681
+ "eval_loss": 1.7257907390594482,
682
+ "eval_rouge1": 0.6543238897579965,
683
+ "eval_rouge2": 0.3606726049451984,
684
+ "eval_rougeL": 0.5317585887753791,
685
+ "eval_rougeLsum": 0.6452028420624081,
686
+ "eval_runtime": 15.0268,
687
+ "eval_samples_per_second": 0.665,
688
+ "eval_steps_per_second": 0.333,
689
+ "step": 6800
690
+ },
691
+ {
692
+ "epoch": 0.8,
693
+ "grad_norm": 0.2579711079597473,
694
+ "learning_rate": 0.00016015039735665254,
695
+ "loss": 1.6316,
696
+ "step": 7000
697
+ },
698
+ {
699
+ "epoch": 0.8,
700
+ "eval_bertscore": 0.7375612854957581,
701
+ "eval_loss": 1.7296981811523438,
702
+ "eval_rouge1": 0.658906725408624,
703
+ "eval_rouge2": 0.35825094165644866,
704
+ "eval_rougeL": 0.5323299193377959,
705
+ "eval_rougeLsum": 0.6500364347290426,
706
+ "eval_runtime": 14.9244,
707
+ "eval_samples_per_second": 0.67,
708
+ "eval_steps_per_second": 0.335,
709
+ "step": 7000
710
+ },
711
+ {
712
+ "epoch": 0.82,
713
+ "grad_norm": 0.2589207589626312,
714
+ "learning_rate": 0.0001590110234426183,
715
+ "loss": 1.6432,
716
+ "step": 7200
717
+ },
718
+ {
719
+ "epoch": 0.82,
720
+ "eval_bertscore": 0.735145092010498,
721
+ "eval_loss": 1.72720205783844,
722
+ "eval_rouge1": 0.6678646250245518,
723
+ "eval_rouge2": 0.36332843150846983,
724
+ "eval_rougeL": 0.537576430733886,
725
+ "eval_rougeLsum": 0.6579789388660506,
726
+ "eval_runtime": 14.9067,
727
+ "eval_samples_per_second": 0.671,
728
+ "eval_steps_per_second": 0.335,
729
+ "step": 7200
730
+ },
731
+ {
732
+ "epoch": 0.84,
733
+ "grad_norm": 0.26652559638023376,
734
+ "learning_rate": 0.00015787164952858404,
735
+ "loss": 1.6488,
736
+ "step": 7400
737
+ },
738
+ {
739
+ "epoch": 0.84,
740
+ "eval_bertscore": 0.7320755124092102,
741
+ "eval_loss": 1.7282931804656982,
742
+ "eval_rouge1": 0.6325633297780734,
743
+ "eval_rouge2": 0.34505856555703185,
744
+ "eval_rougeL": 0.5100006743383693,
745
+ "eval_rougeLsum": 0.6230385336341938,
746
+ "eval_runtime": 14.9075,
747
+ "eval_samples_per_second": 0.671,
748
+ "eval_steps_per_second": 0.335,
749
+ "step": 7400
750
+ },
751
+ {
752
+ "epoch": 0.87,
753
+ "grad_norm": 0.27353721857070923,
754
+ "learning_rate": 0.00015673227561454982,
755
+ "loss": 1.6486,
756
+ "step": 7600
757
+ },
758
+ {
759
+ "epoch": 0.87,
760
+ "eval_bertscore": 0.7367390394210815,
761
+ "eval_loss": 1.7290785312652588,
762
+ "eval_rouge1": 0.639487116874423,
763
+ "eval_rouge2": 0.3466574229736927,
764
+ "eval_rougeL": 0.515038120249177,
765
+ "eval_rougeLsum": 0.6301157215372983,
766
+ "eval_runtime": 15.0876,
767
+ "eval_samples_per_second": 0.663,
768
+ "eval_steps_per_second": 0.331,
769
+ "step": 7600
770
+ },
771
+ {
772
+ "epoch": 0.89,
773
+ "grad_norm": 0.24777938425540924,
774
+ "learning_rate": 0.00015559290170051558,
775
+ "loss": 1.6271,
776
+ "step": 7800
777
+ },
778
+ {
779
+ "epoch": 0.89,
780
+ "eval_bertscore": 0.735866904258728,
781
+ "eval_loss": 1.7264015674591064,
782
+ "eval_rouge1": 0.64939597901302,
783
+ "eval_rouge2": 0.3554282813944538,
784
+ "eval_rougeL": 0.5247953329477759,
785
+ "eval_rougeLsum": 0.6405524812915908,
786
+ "eval_runtime": 14.8892,
787
+ "eval_samples_per_second": 0.672,
788
+ "eval_steps_per_second": 0.336,
789
+ "step": 7800
790
+ },
791
+ {
792
+ "epoch": 0.91,
793
+ "grad_norm": 0.2703794538974762,
794
+ "learning_rate": 0.00015445352778648136,
795
+ "loss": 1.6415,
796
+ "step": 8000
797
+ },
798
+ {
799
+ "epoch": 0.91,
800
+ "eval_bertscore": 0.7325771450996399,
801
+ "eval_loss": 1.7271970510482788,
802
+ "eval_rouge1": 0.6659432894288253,
803
+ "eval_rouge2": 0.35962933912652617,
804
+ "eval_rougeL": 0.5385420432813512,
805
+ "eval_rougeLsum": 0.6557027031484046,
806
+ "eval_runtime": 14.8319,
807
+ "eval_samples_per_second": 0.674,
808
+ "eval_steps_per_second": 0.337,
809
+ "step": 8000
810
+ },
811
+ {
812
+ "epoch": 0.93,
813
+ "grad_norm": 0.28753793239593506,
814
+ "learning_rate": 0.0001533141538724471,
815
+ "loss": 1.6239,
816
+ "step": 8200
817
+ },
818
+ {
819
+ "epoch": 0.93,
820
+ "eval_bertscore": 0.7350013852119446,
821
+ "eval_loss": 1.7266199588775635,
822
+ "eval_rouge1": 0.6549282561414593,
823
+ "eval_rouge2": 0.35694530595734475,
824
+ "eval_rougeL": 0.5301601006964574,
825
+ "eval_rougeLsum": 0.6441779306137909,
826
+ "eval_runtime": 14.9005,
827
+ "eval_samples_per_second": 0.671,
828
+ "eval_steps_per_second": 0.336,
829
+ "step": 8200
830
+ },
831
+ {
832
+ "epoch": 0.96,
833
+ "grad_norm": 0.23870150744915009,
834
+ "learning_rate": 0.00015217477995841286,
835
+ "loss": 1.6293,
836
+ "step": 8400
837
+ },
838
+ {
839
+ "epoch": 0.96,
840
+ "eval_bertscore": 0.7271261811256409,
841
+ "eval_loss": 1.7256368398666382,
842
+ "eval_rouge1": 0.6515513829901936,
843
+ "eval_rouge2": 0.35217616104918836,
844
+ "eval_rougeL": 0.5236553509227138,
845
+ "eval_rougeLsum": 0.6411473505324752,
846
+ "eval_runtime": 14.9938,
847
+ "eval_samples_per_second": 0.667,
848
+ "eval_steps_per_second": 0.333,
849
+ "step": 8400
850
+ },
851
+ {
852
+ "epoch": 0.98,
853
+ "grad_norm": 0.28276997804641724,
854
+ "learning_rate": 0.00015103540604437861,
855
+ "loss": 1.6242,
856
+ "step": 8600
857
+ },
858
+ {
859
+ "epoch": 0.98,
860
+ "eval_bertscore": 0.7347334027290344,
861
+ "eval_loss": 1.717627763748169,
862
+ "eval_rouge1": 0.6350112495847634,
863
+ "eval_rouge2": 0.3477570751550898,
864
+ "eval_rougeL": 0.5146616989899861,
865
+ "eval_rougeLsum": 0.6246669376525157,
866
+ "eval_runtime": 15.7032,
867
+ "eval_samples_per_second": 0.637,
868
+ "eval_steps_per_second": 0.318,
869
+ "step": 8600
870
+ },
871
+ {
872
+ "epoch": 1.0,
873
+ "grad_norm": 0.24915842711925507,
874
+ "learning_rate": 0.00014989603213034437,
875
+ "loss": 1.6245,
876
+ "step": 8800
877
+ },
878
+ {
879
+ "epoch": 1.0,
880
+ "eval_bertscore": 0.7313701510429382,
881
+ "eval_loss": 1.7292964458465576,
882
+ "eval_rouge1": 0.6479528105367669,
883
+ "eval_rouge2": 0.35020983244262877,
884
+ "eval_rougeL": 0.5200907337780047,
885
+ "eval_rougeLsum": 0.6372896614836894,
886
+ "eval_runtime": 15.0043,
887
+ "eval_samples_per_second": 0.666,
888
+ "eval_steps_per_second": 0.333,
889
+ "step": 8800
890
+ },
891
+ {
892
+ "epoch": 1.03,
893
+ "grad_norm": 0.24036027491092682,
894
+ "learning_rate": 0.00014875665821631015,
895
+ "loss": 1.5364,
896
+ "step": 9000
897
+ },
898
+ {
899
+ "epoch": 1.03,
900
+ "eval_bertscore": 0.7327737808227539,
901
+ "eval_loss": 1.7339435815811157,
902
+ "eval_rouge1": 0.6568524178922349,
903
+ "eval_rouge2": 0.35560270713543163,
904
+ "eval_rougeL": 0.5310443670833082,
905
+ "eval_rougeLsum": 0.6480993679097387,
906
+ "eval_runtime": 14.9303,
907
+ "eval_samples_per_second": 0.67,
908
+ "eval_steps_per_second": 0.335,
909
+ "step": 9000
910
+ },
911
+ {
912
+ "epoch": 1.05,
913
+ "grad_norm": 0.2729027271270752,
914
+ "learning_rate": 0.0001476172843022759,
915
+ "loss": 1.5182,
916
+ "step": 9200
917
+ },
918
+ {
919
+ "epoch": 1.05,
920
+ "eval_bertscore": 0.7334672212600708,
921
+ "eval_loss": 1.739061713218689,
922
+ "eval_rouge1": 0.6552962187824329,
923
+ "eval_rouge2": 0.35210314124279196,
924
+ "eval_rougeL": 0.5272039052368354,
925
+ "eval_rougeLsum": 0.6437473533492806,
926
+ "eval_runtime": 15.5418,
927
+ "eval_samples_per_second": 0.643,
928
+ "eval_steps_per_second": 0.322,
929
+ "step": 9200
930
+ },
931
+ {
932
+ "epoch": 1.07,
933
+ "grad_norm": 0.2909716069698334,
934
+ "learning_rate": 0.00014647791038824168,
935
+ "loss": 1.5276,
936
+ "step": 9400
937
+ },
938
+ {
939
+ "epoch": 1.07,
940
+ "eval_bertscore": 0.7288902997970581,
941
+ "eval_loss": 1.736944556236267,
942
+ "eval_rouge1": 0.6533271685598301,
943
+ "eval_rouge2": 0.35279315321532184,
944
+ "eval_rougeL": 0.5262688234671329,
945
+ "eval_rougeLsum": 0.6424084937151033,
946
+ "eval_runtime": 15.1115,
947
+ "eval_samples_per_second": 0.662,
948
+ "eval_steps_per_second": 0.331,
949
+ "step": 9400
950
+ },
951
+ {
952
+ "epoch": 1.09,
953
+ "grad_norm": 0.3035859763622284,
954
+ "learning_rate": 0.00014533853647420743,
955
+ "loss": 1.5445,
956
+ "step": 9600
957
+ },
958
+ {
959
+ "epoch": 1.09,
960
+ "eval_bertscore": 0.7308284044265747,
961
+ "eval_loss": 1.737762689590454,
962
+ "eval_rouge1": 0.6619725777891359,
963
+ "eval_rouge2": 0.3611963714506864,
964
+ "eval_rougeL": 0.5363802967084452,
965
+ "eval_rougeLsum": 0.6516690557971352,
966
+ "eval_runtime": 14.9932,
967
+ "eval_samples_per_second": 0.667,
968
+ "eval_steps_per_second": 0.333,
969
+ "step": 9600
970
+ },
971
+ {
972
+ "epoch": 1.12,
973
+ "grad_norm": 0.26574915647506714,
974
+ "learning_rate": 0.0001441991625601732,
975
+ "loss": 1.5342,
976
+ "step": 9800
977
+ },
978
+ {
979
+ "epoch": 1.12,
980
+ "eval_bertscore": 0.7328712344169617,
981
+ "eval_loss": 1.7393991947174072,
982
+ "eval_rouge1": 0.6856504003396884,
983
+ "eval_rouge2": 0.3761098841062477,
984
+ "eval_rougeL": 0.555477293163325,
985
+ "eval_rougeLsum": 0.6757574283262289,
986
+ "eval_runtime": 14.8121,
987
+ "eval_samples_per_second": 0.675,
988
+ "eval_steps_per_second": 0.338,
989
+ "step": 9800
990
+ },
991
+ {
992
+ "epoch": 1.14,
993
+ "grad_norm": 0.315468430519104,
994
+ "learning_rate": 0.00014305978864613897,
995
+ "loss": 1.543,
996
+ "step": 10000
997
+ },
998
+ {
999
+ "epoch": 1.14,
1000
+ "eval_bertscore": 0.7349387407302856,
1001
+ "eval_loss": 1.7352710962295532,
1002
+ "eval_rouge1": 0.6749953128982036,
1003
+ "eval_rouge2": 0.3720385250530084,
1004
+ "eval_rougeL": 0.5472261566474382,
1005
+ "eval_rougeLsum": 0.6657643539219252,
1006
+ "eval_runtime": 14.909,
1007
+ "eval_samples_per_second": 0.671,
1008
+ "eval_steps_per_second": 0.335,
1009
+ "step": 10000
1010
+ },
1011
+ {
1012
+ "epoch": 1.16,
1013
+ "grad_norm": 0.29815027117729187,
1014
+ "learning_rate": 0.00014192041473210472,
1015
+ "loss": 1.5547,
1016
+ "step": 10200
1017
+ },
1018
+ {
1019
+ "epoch": 1.16,
1020
+ "eval_bertscore": 0.7359883189201355,
1021
+ "eval_loss": 1.7269136905670166,
1022
+ "eval_rouge1": 0.6561141614088863,
1023
+ "eval_rouge2": 0.3606175666303814,
1024
+ "eval_rougeL": 0.5302270771032793,
1025
+ "eval_rougeLsum": 0.6446912079521883,
1026
+ "eval_runtime": 14.9527,
1027
+ "eval_samples_per_second": 0.669,
1028
+ "eval_steps_per_second": 0.334,
1029
+ "step": 10200
1030
+ },
1031
+ {
1032
+ "epoch": 1.18,
1033
+ "grad_norm": 0.3595702350139618,
1034
+ "learning_rate": 0.00014078104081807047,
1035
+ "loss": 1.5567,
1036
+ "step": 10400
1037
+ },
1038
+ {
1039
+ "epoch": 1.18,
1040
+ "eval_bertscore": 0.7328116297721863,
1041
+ "eval_loss": 1.7341644763946533,
1042
+ "eval_rouge1": 0.6420332714823549,
1043
+ "eval_rouge2": 0.35094864549032,
1044
+ "eval_rougeL": 0.5179556761398367,
1045
+ "eval_rougeLsum": 0.631987397226809,
1046
+ "eval_runtime": 15.1438,
1047
+ "eval_samples_per_second": 0.66,
1048
+ "eval_steps_per_second": 0.33,
1049
+ "step": 10400
1050
+ },
1051
+ {
1052
+ "epoch": 1.21,
1053
+ "grad_norm": 0.2718666195869446,
1054
+ "learning_rate": 0.00013964166690403623,
1055
+ "loss": 1.5408,
1056
+ "step": 10600
1057
+ },
1058
+ {
1059
+ "epoch": 1.21,
1060
+ "eval_bertscore": 0.7337731122970581,
1061
+ "eval_loss": 1.7330901622772217,
1062
+ "eval_rouge1": 0.661681342484687,
1063
+ "eval_rouge2": 0.3626833509973693,
1064
+ "eval_rougeL": 0.5329424447373774,
1065
+ "eval_rougeLsum": 0.6519750177144633,
1066
+ "eval_runtime": 14.8142,
1067
+ "eval_samples_per_second": 0.675,
1068
+ "eval_steps_per_second": 0.338,
1069
+ "step": 10600
1070
+ },
1071
+ {
1072
+ "epoch": 1.23,
1073
+ "grad_norm": 0.29183274507522583,
1074
+ "learning_rate": 0.00013850229299000198,
1075
+ "loss": 1.5422,
1076
+ "step": 10800
1077
+ },
1078
+ {
1079
+ "epoch": 1.23,
1080
+ "eval_bertscore": 0.7331051230430603,
1081
+ "eval_loss": 1.7297636270523071,
1082
+ "eval_rouge1": 0.6655497978238063,
1083
+ "eval_rouge2": 0.3614235788441926,
1084
+ "eval_rougeL": 0.5327210061667442,
1085
+ "eval_rougeLsum": 0.6548836840483913,
1086
+ "eval_runtime": 15.1359,
1087
+ "eval_samples_per_second": 0.661,
1088
+ "eval_steps_per_second": 0.33,
1089
+ "step": 10800
1090
+ },
1091
+ {
1092
+ "epoch": 1.25,
1093
+ "grad_norm": 0.30979740619659424,
1094
+ "learning_rate": 0.00013736291907596776,
1095
+ "loss": 1.5372,
1096
+ "step": 11000
1097
+ },
1098
+ {
1099
+ "epoch": 1.25,
1100
+ "eval_bertscore": 0.7312799692153931,
1101
+ "eval_loss": 1.732444167137146,
1102
+ "eval_rouge1": 0.6568292865033993,
1103
+ "eval_rouge2": 0.35876682221562006,
1104
+ "eval_rougeL": 0.5300878844981931,
1105
+ "eval_rougeLsum": 0.6461751645858989,
1106
+ "eval_runtime": 14.819,
1107
+ "eval_samples_per_second": 0.675,
1108
+ "eval_steps_per_second": 0.337,
1109
+ "step": 11000
1110
+ },
1111
+ {
1112
+ "epoch": 1.28,
1113
+ "grad_norm": 0.31343138217926025,
1114
+ "learning_rate": 0.0001362235451619335,
1115
+ "loss": 1.5301,
1116
+ "step": 11200
1117
+ },
1118
+ {
1119
+ "epoch": 1.28,
1120
+ "eval_bertscore": 0.7317885160446167,
1121
+ "eval_loss": 1.7358499765396118,
1122
+ "eval_rouge1": 0.6548673097943329,
1123
+ "eval_rouge2": 0.3609116081432997,
1124
+ "eval_rougeL": 0.5279887650752133,
1125
+ "eval_rougeLsum": 0.6466232329097188,
1126
+ "eval_runtime": 14.8259,
1127
+ "eval_samples_per_second": 0.674,
1128
+ "eval_steps_per_second": 0.337,
1129
+ "step": 11200
1130
+ },
1131
+ {
1132
+ "epoch": 1.3,
1133
+ "grad_norm": 0.36181533336639404,
1134
+ "learning_rate": 0.0001350841712478993,
1135
+ "loss": 1.5421,
1136
+ "step": 11400
1137
+ },
1138
+ {
1139
+ "epoch": 1.3,
1140
+ "eval_bertscore": 0.7316756248474121,
1141
+ "eval_loss": 1.7282969951629639,
1142
+ "eval_rouge1": 0.6551882964480251,
1143
+ "eval_rouge2": 0.3580708921400697,
1144
+ "eval_rougeL": 0.5255367305995147,
1145
+ "eval_rougeLsum": 0.6449192953008009,
1146
+ "eval_runtime": 14.8816,
1147
+ "eval_samples_per_second": 0.672,
1148
+ "eval_steps_per_second": 0.336,
1149
+ "step": 11400
1150
+ },
1151
+ {
1152
+ "epoch": 1.32,
1153
+ "grad_norm": 0.30600836873054504,
1154
+ "learning_rate": 0.00013394479733386505,
1155
+ "loss": 1.5538,
1156
+ "step": 11600
1157
+ },
1158
+ {
1159
+ "epoch": 1.32,
1160
+ "eval_bertscore": 0.7311854362487793,
1161
+ "eval_loss": 1.7313562631607056,
1162
+ "eval_rouge1": 0.6592751199424156,
1163
+ "eval_rouge2": 0.35802855072854206,
1164
+ "eval_rougeL": 0.5297288176377084,
1165
+ "eval_rougeLsum": 0.6489455314962717,
1166
+ "eval_runtime": 15.0693,
1167
+ "eval_samples_per_second": 0.664,
1168
+ "eval_steps_per_second": 0.332,
1169
+ "step": 11600
1170
+ },
1171
+ {
1172
+ "epoch": 1.34,
1173
+ "grad_norm": 0.29904893040657043,
1174
+ "learning_rate": 0.0001328054234198308,
1175
+ "loss": 1.5328,
1176
+ "step": 11800
1177
+ },
1178
+ {
1179
+ "epoch": 1.34,
1180
+ "eval_bertscore": 0.7312635183334351,
1181
+ "eval_loss": 1.7318429946899414,
1182
+ "eval_rouge1": 0.6577169369077195,
1183
+ "eval_rouge2": 0.3582474830918887,
1184
+ "eval_rougeL": 0.5314990647771975,
1185
+ "eval_rougeLsum": 0.6454785220479866,
1186
+ "eval_runtime": 15.0235,
1187
+ "eval_samples_per_second": 0.666,
1188
+ "eval_steps_per_second": 0.333,
1189
+ "step": 11800
1190
+ },
1191
+ {
1192
+ "epoch": 1.37,
1193
+ "grad_norm": 0.3025416433811188,
1194
+ "learning_rate": 0.00013166604950579658,
1195
+ "loss": 1.5349,
1196
+ "step": 12000
1197
+ },
1198
+ {
1199
+ "epoch": 1.37,
1200
+ "eval_bertscore": 0.7325812578201294,
1201
+ "eval_loss": 1.7309118509292603,
1202
+ "eval_rouge1": 0.6629133074951261,
1203
+ "eval_rouge2": 0.3678158453940578,
1204
+ "eval_rougeL": 0.5380936907276155,
1205
+ "eval_rougeLsum": 0.654883061928214,
1206
+ "eval_runtime": 14.7666,
1207
+ "eval_samples_per_second": 0.677,
1208
+ "eval_steps_per_second": 0.339,
1209
+ "step": 12000
1210
+ },
1211
+ {
1212
+ "epoch": 1.39,
1213
+ "grad_norm": 0.34982389211654663,
1214
+ "learning_rate": 0.00013052667559176233,
1215
+ "loss": 1.5513,
1216
+ "step": 12200
1217
+ },
1218
+ {
1219
+ "epoch": 1.39,
1220
+ "eval_bertscore": 0.7340582609176636,
1221
+ "eval_loss": 1.7363474369049072,
1222
+ "eval_rouge1": 0.6555817937418287,
1223
+ "eval_rouge2": 0.35630500078358396,
1224
+ "eval_rougeL": 0.5272412353478366,
1225
+ "eval_rougeLsum": 0.6445837479327643,
1226
+ "eval_runtime": 14.9664,
1227
+ "eval_samples_per_second": 0.668,
1228
+ "eval_steps_per_second": 0.334,
1229
+ "step": 12200
1230
+ },
1231
+ {
1232
+ "epoch": 1.41,
1233
+ "grad_norm": 0.35809043049812317,
1234
+ "learning_rate": 0.0001293873016777281,
1235
+ "loss": 1.5444,
1236
+ "step": 12400
1237
+ },
1238
+ {
1239
+ "epoch": 1.41,
1240
+ "eval_bertscore": 0.7334069013595581,
1241
+ "eval_loss": 1.7328729629516602,
1242
+ "eval_rouge1": 0.6617971237669364,
1243
+ "eval_rouge2": 0.35951260376512423,
1244
+ "eval_rougeL": 0.5345512305507059,
1245
+ "eval_rougeLsum": 0.648363531132752,
1246
+ "eval_runtime": 15.2146,
1247
+ "eval_samples_per_second": 0.657,
1248
+ "eval_steps_per_second": 0.329,
1249
+ "step": 12400
1250
+ },
1251
+ {
1252
+ "epoch": 1.44,
1253
+ "grad_norm": 0.2954196631908417,
1254
+ "learning_rate": 0.00012824792776369387,
1255
+ "loss": 1.5406,
1256
+ "step": 12600
1257
+ },
1258
+ {
1259
+ "epoch": 1.44,
1260
+ "eval_bertscore": 0.7321678400039673,
1261
+ "eval_loss": 1.7335160970687866,
1262
+ "eval_rouge1": 0.6573625593086756,
1263
+ "eval_rouge2": 0.36210525247389347,
1264
+ "eval_rougeL": 0.5379361120230158,
1265
+ "eval_rougeLsum": 0.6459787883452857,
1266
+ "eval_runtime": 14.8942,
1267
+ "eval_samples_per_second": 0.671,
1268
+ "eval_steps_per_second": 0.336,
1269
+ "step": 12600
1270
+ },
1271
+ {
1272
+ "epoch": 1.46,
1273
+ "grad_norm": 0.32190588116645813,
1274
+ "learning_rate": 0.00012710855384965962,
1275
+ "loss": 1.5491,
1276
+ "step": 12800
1277
+ },
1278
+ {
1279
+ "epoch": 1.46,
1280
+ "eval_bertscore": 0.7346011400222778,
1281
+ "eval_loss": 1.7364966869354248,
1282
+ "eval_rouge1": 0.6481210247390559,
1283
+ "eval_rouge2": 0.3521173896017687,
1284
+ "eval_rougeL": 0.5240500581372636,
1285
+ "eval_rougeLsum": 0.63706442433335,
1286
+ "eval_runtime": 14.923,
1287
+ "eval_samples_per_second": 0.67,
1288
+ "eval_steps_per_second": 0.335,
1289
+ "step": 12800
1290
+ },
1291
+ {
1292
+ "epoch": 1.48,
1293
+ "grad_norm": 0.33323267102241516,
1294
+ "learning_rate": 0.00012596917993562537,
1295
+ "loss": 1.5596,
1296
+ "step": 13000
1297
+ },
1298
+ {
1299
+ "epoch": 1.48,
1300
+ "eval_bertscore": 0.7331587076187134,
1301
+ "eval_loss": 1.7332260608673096,
1302
+ "eval_rouge1": 0.6561257401878793,
1303
+ "eval_rouge2": 0.3548063723792664,
1304
+ "eval_rougeL": 0.527807776001489,
1305
+ "eval_rougeLsum": 0.6451911907984706,
1306
+ "eval_runtime": 15.4703,
1307
+ "eval_samples_per_second": 0.646,
1308
+ "eval_steps_per_second": 0.323,
1309
+ "step": 13000
1310
+ },
1311
+ {
1312
+ "epoch": 1.5,
1313
+ "grad_norm": 0.3564057946205139,
1314
+ "learning_rate": 0.00012482980602159113,
1315
+ "loss": 1.5261,
1316
+ "step": 13200
1317
+ },
1318
+ {
1319
+ "epoch": 1.5,
1320
+ "eval_bertscore": 0.7306063771247864,
1321
+ "eval_loss": 1.7368810176849365,
1322
+ "eval_rouge1": 0.637722723890071,
1323
+ "eval_rouge2": 0.3455358728458236,
1324
+ "eval_rougeL": 0.5136372690435154,
1325
+ "eval_rougeLsum": 0.6273570573595115,
1326
+ "eval_runtime": 15.3533,
1327
+ "eval_samples_per_second": 0.651,
1328
+ "eval_steps_per_second": 0.326,
1329
+ "step": 13200
1330
+ },
1331
+ {
1332
+ "epoch": 1.53,
1333
+ "grad_norm": 0.29219934344291687,
1334
+ "learning_rate": 0.0001236904321075569,
1335
+ "loss": 1.519,
1336
+ "step": 13400
1337
+ },
1338
+ {
1339
+ "epoch": 1.53,
1340
+ "eval_bertscore": 0.7338696122169495,
1341
+ "eval_loss": 1.734724998474121,
1342
+ "eval_rouge1": 0.6442107446420164,
1343
+ "eval_rouge2": 0.3494748457109431,
1344
+ "eval_rougeL": 0.5207483892007314,
1345
+ "eval_rougeLsum": 0.632886404907802,
1346
+ "eval_runtime": 15.3077,
1347
+ "eval_samples_per_second": 0.653,
1348
+ "eval_steps_per_second": 0.327,
1349
+ "step": 13400
1350
+ },
1351
+ {
1352
+ "epoch": 1.55,
1353
+ "grad_norm": 0.34681758284568787,
1354
+ "learning_rate": 0.00012255105819352266,
1355
+ "loss": 1.5419,
1356
+ "step": 13600
1357
+ },
1358
+ {
1359
+ "epoch": 1.55,
1360
+ "eval_bertscore": 0.7350045442581177,
1361
+ "eval_loss": 1.7329858541488647,
1362
+ "eval_rouge1": 0.6606839869796519,
1363
+ "eval_rouge2": 0.362188561160822,
1364
+ "eval_rougeL": 0.5342033818317451,
1365
+ "eval_rougeLsum": 0.6493340000068861,
1366
+ "eval_runtime": 15.44,
1367
+ "eval_samples_per_second": 0.648,
1368
+ "eval_steps_per_second": 0.324,
1369
+ "step": 13600
1370
+ },
1371
+ {
1372
+ "epoch": 1.57,
1373
+ "grad_norm": 0.3043666481971741,
1374
+ "learning_rate": 0.00012141168427948844,
1375
+ "loss": 1.5402,
1376
+ "step": 13800
1377
+ },
1378
+ {
1379
+ "epoch": 1.57,
1380
+ "eval_bertscore": 0.7363221645355225,
1381
+ "eval_loss": 1.7308530807495117,
1382
+ "eval_rouge1": 0.6638252384356028,
1383
+ "eval_rouge2": 0.3643237697892826,
1384
+ "eval_rougeL": 0.5403775887381331,
1385
+ "eval_rougeLsum": 0.6537260000827279,
1386
+ "eval_runtime": 14.7668,
1387
+ "eval_samples_per_second": 0.677,
1388
+ "eval_steps_per_second": 0.339,
1389
+ "step": 13800
1390
+ },
1391
+ {
1392
+ "epoch": 1.59,
1393
+ "grad_norm": 0.4073585867881775,
1394
+ "learning_rate": 0.00012027231036545419,
1395
+ "loss": 1.5256,
1396
+ "step": 14000
1397
+ },
1398
+ {
1399
+ "epoch": 1.59,
1400
+ "eval_bertscore": 0.7310279607772827,
1401
+ "eval_loss": 1.7326784133911133,
1402
+ "eval_rouge1": 0.6609594314120198,
1403
+ "eval_rouge2": 0.3601530714440473,
1404
+ "eval_rougeL": 0.5344452687135626,
1405
+ "eval_rougeLsum": 0.6480936554342305,
1406
+ "eval_runtime": 14.8565,
1407
+ "eval_samples_per_second": 0.673,
1408
+ "eval_steps_per_second": 0.337,
1409
+ "step": 14000
1410
+ },
1411
+ {
1412
+ "epoch": 1.62,
1413
+ "grad_norm": 0.3211813271045685,
1414
+ "learning_rate": 0.00011913293645141995,
1415
+ "loss": 1.5366,
1416
+ "step": 14200
1417
+ },
1418
+ {
1419
+ "epoch": 1.62,
1420
+ "eval_bertscore": 0.7356667518615723,
1421
+ "eval_loss": 1.7280094623565674,
1422
+ "eval_rouge1": 0.6519353227375031,
1423
+ "eval_rouge2": 0.3587025716186173,
1424
+ "eval_rougeL": 0.5306356200586075,
1425
+ "eval_rougeLsum": 0.6408870347994059,
1426
+ "eval_runtime": 14.9264,
1427
+ "eval_samples_per_second": 0.67,
1428
+ "eval_steps_per_second": 0.335,
1429
+ "step": 14200
1430
+ },
1431
+ {
1432
+ "epoch": 1.64,
1433
+ "grad_norm": 0.32776832580566406,
1434
+ "learning_rate": 0.00011799356253738571,
1435
+ "loss": 1.5504,
1436
+ "step": 14400
1437
+ },
1438
+ {
1439
+ "epoch": 1.64,
1440
+ "eval_bertscore": 0.7331353425979614,
1441
+ "eval_loss": 1.7308950424194336,
1442
+ "eval_rouge1": 0.6627702292814652,
1443
+ "eval_rouge2": 0.36117793957379707,
1444
+ "eval_rougeL": 0.5369305446079228,
1445
+ "eval_rougeLsum": 0.6516924083980089,
1446
+ "eval_runtime": 16.0138,
1447
+ "eval_samples_per_second": 0.624,
1448
+ "eval_steps_per_second": 0.312,
1449
+ "step": 14400
1450
+ },
1451
+ {
1452
+ "epoch": 1.66,
1453
+ "grad_norm": 0.3209726810455322,
1454
+ "learning_rate": 0.00011685418862335147,
1455
+ "loss": 1.5473,
1456
+ "step": 14600
1457
+ },
1458
+ {
1459
+ "epoch": 1.66,
1460
+ "eval_bertscore": 0.732498824596405,
1461
+ "eval_loss": 1.7328402996063232,
1462
+ "eval_rouge1": 0.6482679740803596,
1463
+ "eval_rouge2": 0.3538726087405498,
1464
+ "eval_rougeL": 0.5267677183598017,
1465
+ "eval_rougeLsum": 0.6366529460029322,
1466
+ "eval_runtime": 15.0195,
1467
+ "eval_samples_per_second": 0.666,
1468
+ "eval_steps_per_second": 0.333,
1469
+ "step": 14600
1470
+ },
1471
+ {
1472
+ "epoch": 1.69,
1473
+ "grad_norm": 0.3174591064453125,
1474
+ "learning_rate": 0.00011571481470931725,
1475
+ "loss": 1.5568,
1476
+ "step": 14800
1477
+ },
1478
+ {
1479
+ "epoch": 1.69,
1480
+ "eval_bertscore": 0.7335298657417297,
1481
+ "eval_loss": 1.7310253381729126,
1482
+ "eval_rouge1": 0.6560468577439627,
1483
+ "eval_rouge2": 0.36039371229175,
1484
+ "eval_rougeL": 0.5318708569729291,
1485
+ "eval_rougeLsum": 0.6444857558837042,
1486
+ "eval_runtime": 14.9774,
1487
+ "eval_samples_per_second": 0.668,
1488
+ "eval_steps_per_second": 0.334,
1489
+ "step": 14800
1490
+ },
1491
+ {
1492
+ "epoch": 1.71,
1493
+ "grad_norm": 0.2936408817768097,
1494
+ "learning_rate": 0.000114575440795283,
1495
+ "loss": 1.5345,
1496
+ "step": 15000
1497
+ },
1498
+ {
1499
+ "epoch": 1.71,
1500
+ "eval_bertscore": 0.7322725057601929,
1501
+ "eval_loss": 1.7270629405975342,
1502
+ "eval_rouge1": 0.6387060930656672,
1503
+ "eval_rouge2": 0.3480508127989137,
1504
+ "eval_rougeL": 0.5148670834213287,
1505
+ "eval_rougeLsum": 0.6273654952601909,
1506
+ "eval_runtime": 15.6687,
1507
+ "eval_samples_per_second": 0.638,
1508
+ "eval_steps_per_second": 0.319,
1509
+ "step": 15000
1510
+ },
1511
+ {
1512
+ "epoch": 1.73,
1513
+ "grad_norm": 0.32960689067840576,
1514
+ "learning_rate": 0.00011343606688124875,
1515
+ "loss": 1.5362,
1516
+ "step": 15200
1517
+ },
1518
+ {
1519
+ "epoch": 1.73,
1520
+ "eval_bertscore": 0.7337037920951843,
1521
+ "eval_loss": 1.7287395000457764,
1522
+ "eval_rouge1": 0.6476816970229771,
1523
+ "eval_rouge2": 0.3532248216683249,
1524
+ "eval_rougeL": 0.5253136618838716,
1525
+ "eval_rougeLsum": 0.6347493764394183,
1526
+ "eval_runtime": 15.0045,
1527
+ "eval_samples_per_second": 0.666,
1528
+ "eval_steps_per_second": 0.333,
1529
+ "step": 15200
1530
+ },
1531
+ {
1532
+ "epoch": 1.75,
1533
+ "grad_norm": 0.33265602588653564,
1534
+ "learning_rate": 0.00011229669296721452,
1535
+ "loss": 1.5215,
1536
+ "step": 15400
1537
+ },
1538
+ {
1539
+ "epoch": 1.75,
1540
+ "eval_bertscore": 0.7330806851387024,
1541
+ "eval_loss": 1.7265052795410156,
1542
+ "eval_rouge1": 0.6529393512177359,
1543
+ "eval_rouge2": 0.36182153145062224,
1544
+ "eval_rougeL": 0.5317061134915853,
1545
+ "eval_rougeLsum": 0.6413066299251913,
1546
+ "eval_runtime": 15.0256,
1547
+ "eval_samples_per_second": 0.666,
1548
+ "eval_steps_per_second": 0.333,
1549
+ "step": 15400
1550
+ },
1551
+ {
1552
+ "epoch": 1.78,
1553
+ "grad_norm": 0.3436201512813568,
1554
+ "learning_rate": 0.00011115731905318027,
1555
+ "loss": 1.539,
1556
+ "step": 15600
1557
+ },
1558
+ {
1559
+ "epoch": 1.78,
1560
+ "eval_bertscore": 0.7335551977157593,
1561
+ "eval_loss": 1.7254730463027954,
1562
+ "eval_rouge1": 0.6388518781767971,
1563
+ "eval_rouge2": 0.3501853846588857,
1564
+ "eval_rougeL": 0.5196828245794569,
1565
+ "eval_rougeLsum": 0.629333993884722,
1566
+ "eval_runtime": 15.2595,
1567
+ "eval_samples_per_second": 0.655,
1568
+ "eval_steps_per_second": 0.328,
1569
+ "step": 15600
1570
+ },
1571
+ {
1572
+ "epoch": 1.8,
1573
+ "grad_norm": 0.3428190350532532,
1574
+ "learning_rate": 0.00011001794513914605,
1575
+ "loss": 1.5273,
1576
+ "step": 15800
1577
+ },
1578
+ {
1579
+ "epoch": 1.8,
1580
+ "eval_bertscore": 0.7331770658493042,
1581
+ "eval_loss": 1.7286018133163452,
1582
+ "eval_rouge1": 0.6581941047310954,
1583
+ "eval_rouge2": 0.36277983926897583,
1584
+ "eval_rougeL": 0.5336464680120501,
1585
+ "eval_rougeLsum": 0.6489239720278894,
1586
+ "eval_runtime": 14.8252,
1587
+ "eval_samples_per_second": 0.675,
1588
+ "eval_steps_per_second": 0.337,
1589
+ "step": 15800
1590
+ },
1591
+ {
1592
+ "epoch": 1.82,
1593
+ "grad_norm": 0.363164484500885,
1594
+ "learning_rate": 0.0001088785712251118,
1595
+ "loss": 1.5445,
1596
+ "step": 16000
1597
+ },
1598
+ {
1599
+ "epoch": 1.82,
1600
+ "eval_bertscore": 0.7377282977104187,
1601
+ "eval_loss": 1.7363064289093018,
1602
+ "eval_rouge1": 0.6547011011872876,
1603
+ "eval_rouge2": 0.3553220826957326,
1604
+ "eval_rougeL": 0.5256073814411315,
1605
+ "eval_rougeLsum": 0.6420095316923398,
1606
+ "eval_runtime": 14.8599,
1607
+ "eval_samples_per_second": 0.673,
1608
+ "eval_steps_per_second": 0.336,
1609
+ "step": 16000
1610
+ },
1611
+ {
1612
+ "epoch": 1.85,
1613
+ "grad_norm": 0.3098333775997162,
1614
+ "learning_rate": 0.00010773919731107757,
1615
+ "loss": 1.5319,
1616
+ "step": 16200
1617
+ },
1618
+ {
1619
+ "epoch": 1.85,
1620
+ "eval_bertscore": 0.7324053645133972,
1621
+ "eval_loss": 1.7284066677093506,
1622
+ "eval_rouge1": 0.6477379941950916,
1623
+ "eval_rouge2": 0.3535918140554809,
1624
+ "eval_rougeL": 0.5226838544730126,
1625
+ "eval_rougeLsum": 0.6373271915355557,
1626
+ "eval_runtime": 14.9318,
1627
+ "eval_samples_per_second": 0.67,
1628
+ "eval_steps_per_second": 0.335,
1629
+ "step": 16200
1630
+ },
1631
+ {
1632
+ "epoch": 1.87,
1633
+ "grad_norm": 0.3637208938598633,
1634
+ "learning_rate": 0.00010659982339704332,
1635
+ "loss": 1.5442,
1636
+ "step": 16400
1637
+ },
1638
+ {
1639
+ "epoch": 1.87,
1640
+ "eval_bertscore": 0.7347462773323059,
1641
+ "eval_loss": 1.7252963781356812,
1642
+ "eval_rouge1": 0.6494449840449819,
1643
+ "eval_rouge2": 0.3586550050575282,
1644
+ "eval_rougeL": 0.5275675395159809,
1645
+ "eval_rougeLsum": 0.6396738714026391,
1646
+ "eval_runtime": 15.2218,
1647
+ "eval_samples_per_second": 0.657,
1648
+ "eval_steps_per_second": 0.328,
1649
+ "step": 16400
1650
+ },
1651
+ {
1652
+ "epoch": 1.89,
1653
+ "grad_norm": 0.35197457671165466,
1654
+ "learning_rate": 0.00010546044948300908,
1655
+ "loss": 1.5131,
1656
+ "step": 16600
1657
+ },
1658
+ {
1659
+ "epoch": 1.89,
1660
+ "eval_bertscore": 0.7329785227775574,
1661
+ "eval_loss": 1.7285687923431396,
1662
+ "eval_rouge1": 0.6582047811143328,
1663
+ "eval_rouge2": 0.3637700686094697,
1664
+ "eval_rougeL": 0.5355021948480279,
1665
+ "eval_rougeLsum": 0.6483245595148677,
1666
+ "eval_runtime": 14.8772,
1667
+ "eval_samples_per_second": 0.672,
1668
+ "eval_steps_per_second": 0.336,
1669
+ "step": 16600
1670
+ },
1671
+ {
1672
+ "epoch": 1.91,
1673
+ "grad_norm": 0.3406757116317749,
1674
+ "learning_rate": 0.00010432107556897486,
1675
+ "loss": 1.5394,
1676
+ "step": 16800
1677
+ },
1678
+ {
1679
+ "epoch": 1.91,
1680
+ "eval_bertscore": 0.7345961332321167,
1681
+ "eval_loss": 1.7324028015136719,
1682
+ "eval_rouge1": 0.6408293615351552,
1683
+ "eval_rouge2": 0.3520120690778129,
1684
+ "eval_rougeL": 0.5145218014745592,
1685
+ "eval_rougeLsum": 0.6297802607384266,
1686
+ "eval_runtime": 15.1044,
1687
+ "eval_samples_per_second": 0.662,
1688
+ "eval_steps_per_second": 0.331,
1689
+ "step": 16800
1690
+ },
1691
+ {
1692
+ "epoch": 1.94,
1693
+ "grad_norm": 0.3417683243751526,
1694
+ "learning_rate": 0.00010318170165494061,
1695
+ "loss": 1.526,
1696
+ "step": 17000
1697
+ },
1698
+ {
1699
+ "epoch": 1.94,
1700
+ "eval_bertscore": 0.735752522945404,
1701
+ "eval_loss": 1.7288110256195068,
1702
+ "eval_rouge1": 0.641158513352794,
1703
+ "eval_rouge2": 0.3544166440855814,
1704
+ "eval_rougeL": 0.5215201980495414,
1705
+ "eval_rougeLsum": 0.630550065494593,
1706
+ "eval_runtime": 15.0797,
1707
+ "eval_samples_per_second": 0.663,
1708
+ "eval_steps_per_second": 0.332,
1709
+ "step": 17000
1710
+ },
1711
+ {
1712
+ "epoch": 1.96,
1713
+ "grad_norm": 0.3256611227989197,
1714
+ "learning_rate": 0.00010204232774090639,
1715
+ "loss": 1.5484,
1716
+ "step": 17200
1717
+ },
1718
+ {
1719
+ "epoch": 1.96,
1720
+ "eval_bertscore": 0.7356327772140503,
1721
+ "eval_loss": 1.7305186986923218,
1722
+ "eval_rouge1": 0.6400269226515611,
1723
+ "eval_rouge2": 0.3502884634173268,
1724
+ "eval_rougeL": 0.517312321281175,
1725
+ "eval_rougeLsum": 0.6284556997614409,
1726
+ "eval_runtime": 15.4097,
1727
+ "eval_samples_per_second": 0.649,
1728
+ "eval_steps_per_second": 0.324,
1729
+ "step": 17200
1730
+ },
1731
+ {
1732
+ "epoch": 1.98,
1733
+ "grad_norm": 0.4035187363624573,
1734
+ "learning_rate": 0.00010090295382687213,
1735
+ "loss": 1.5261,
1736
+ "step": 17400
1737
+ },
1738
+ {
1739
+ "epoch": 1.98,
1740
+ "eval_bertscore": 0.7339992523193359,
1741
+ "eval_loss": 1.7282793521881104,
1742
+ "eval_rouge1": 0.6335770390416183,
1743
+ "eval_rouge2": 0.34592404578075897,
1744
+ "eval_rougeL": 0.5109045259792113,
1745
+ "eval_rougeLsum": 0.6218413683710426,
1746
+ "eval_runtime": 15.1959,
1747
+ "eval_samples_per_second": 0.658,
1748
+ "eval_steps_per_second": 0.329,
1749
+ "step": 17400
1750
+ },
1751
+ {
1752
+ "epoch": 2.0,
1753
+ "grad_norm": 0.34987062215805054,
1754
+ "learning_rate": 9.97635799128379e-05,
1755
+ "loss": 1.5199,
1756
+ "step": 17600
1757
+ },
1758
+ {
1759
+ "epoch": 2.0,
1760
+ "eval_bertscore": 0.7326329946517944,
1761
+ "eval_loss": 1.7544715404510498,
1762
+ "eval_rouge1": 0.6451558045750205,
1763
+ "eval_rouge2": 0.35565806935653943,
1764
+ "eval_rougeL": 0.5217034865840529,
1765
+ "eval_rougeLsum": 0.6329869715356753,
1766
+ "eval_runtime": 15.0351,
1767
+ "eval_samples_per_second": 0.665,
1768
+ "eval_steps_per_second": 0.333,
1769
+ "step": 17600
1770
+ },
1771
+ {
1772
+ "epoch": 2.03,
1773
+ "grad_norm": 0.37184038758277893,
1774
+ "learning_rate": 9.862420599880366e-05,
1775
+ "loss": 1.41,
1776
+ "step": 17800
1777
+ },
1778
+ {
1779
+ "epoch": 2.03,
1780
+ "eval_bertscore": 0.7315141558647156,
1781
+ "eval_loss": 1.7585878372192383,
1782
+ "eval_rouge1": 0.6469319193583706,
1783
+ "eval_rouge2": 0.3514447211469598,
1784
+ "eval_rougeL": 0.524755857688278,
1785
+ "eval_rougeLsum": 0.6350164781858667,
1786
+ "eval_runtime": 14.9583,
1787
+ "eval_samples_per_second": 0.669,
1788
+ "eval_steps_per_second": 0.334,
1789
+ "step": 17800
1790
+ },
1791
+ {
1792
+ "epoch": 2.05,
1793
+ "grad_norm": 0.3812776803970337,
1794
+ "learning_rate": 9.748483208476943e-05,
1795
+ "loss": 1.4132,
1796
+ "step": 18000
1797
+ },
1798
+ {
1799
+ "epoch": 2.05,
1800
+ "eval_bertscore": 0.7335561513900757,
1801
+ "eval_loss": 1.764611840248108,
1802
+ "eval_rouge1": 0.6381916780473581,
1803
+ "eval_rouge2": 0.3482510604092539,
1804
+ "eval_rougeL": 0.5162105225823392,
1805
+ "eval_rougeLsum": 0.627150245441782,
1806
+ "eval_runtime": 15.8515,
1807
+ "eval_samples_per_second": 0.631,
1808
+ "eval_steps_per_second": 0.315,
1809
+ "step": 18000
1810
+ },
1811
+ {
1812
+ "epoch": 2.07,
1813
+ "grad_norm": 0.45525220036506653,
1814
+ "learning_rate": 9.634545817073518e-05,
1815
+ "loss": 1.4,
1816
+ "step": 18200
1817
+ },
1818
+ {
1819
+ "epoch": 2.07,
1820
+ "eval_bertscore": 0.73627769947052,
1821
+ "eval_loss": 1.7585163116455078,
1822
+ "eval_rouge1": 0.6670097658027134,
1823
+ "eval_rouge2": 0.3658295359911405,
1824
+ "eval_rougeL": 0.5429667657900548,
1825
+ "eval_rougeLsum": 0.6543501745791419,
1826
+ "eval_runtime": 15.0301,
1827
+ "eval_samples_per_second": 0.665,
1828
+ "eval_steps_per_second": 0.333,
1829
+ "step": 18200
1830
+ },
1831
+ {
1832
+ "epoch": 2.1,
1833
+ "grad_norm": 0.37322184443473816,
1834
+ "learning_rate": 9.520608425670095e-05,
1835
+ "loss": 1.4293,
1836
+ "step": 18400
1837
+ },
1838
+ {
1839
+ "epoch": 2.1,
1840
+ "eval_bertscore": 0.730435848236084,
1841
+ "eval_loss": 1.764052391052246,
1842
+ "eval_rouge1": 0.6640215078213034,
1843
+ "eval_rouge2": 0.3625932287322054,
1844
+ "eval_rougeL": 0.5379978391335138,
1845
+ "eval_rougeLsum": 0.6542054656293199,
1846
+ "eval_runtime": 15.0762,
1847
+ "eval_samples_per_second": 0.663,
1848
+ "eval_steps_per_second": 0.332,
1849
+ "step": 18400
1850
+ },
1851
+ {
1852
+ "epoch": 2.12,
1853
+ "grad_norm": 0.4260891079902649,
1854
+ "learning_rate": 9.40667103426667e-05,
1855
+ "loss": 1.4077,
1856
+ "step": 18600
1857
+ },
1858
+ {
1859
+ "epoch": 2.12,
1860
+ "eval_bertscore": 0.7309869527816772,
1861
+ "eval_loss": 1.762108564376831,
1862
+ "eval_rouge1": 0.6571171081737958,
1863
+ "eval_rouge2": 0.35780421333141865,
1864
+ "eval_rougeL": 0.5320129270967632,
1865
+ "eval_rougeLsum": 0.64587787409523,
1866
+ "eval_runtime": 14.9004,
1867
+ "eval_samples_per_second": 0.671,
1868
+ "eval_steps_per_second": 0.336,
1869
+ "step": 18600
1870
+ },
1871
+ {
1872
+ "epoch": 2.14,
1873
+ "grad_norm": 0.39479926228523254,
1874
+ "learning_rate": 9.292733642863247e-05,
1875
+ "loss": 1.4165,
1876
+ "step": 18800
1877
+ },
1878
+ {
1879
+ "epoch": 2.14,
1880
+ "eval_bertscore": 0.7324444651603699,
1881
+ "eval_loss": 1.7607113122940063,
1882
+ "eval_rouge1": 0.6628398862884018,
1883
+ "eval_rouge2": 0.3627259806721216,
1884
+ "eval_rougeL": 0.5366106483832656,
1885
+ "eval_rougeLsum": 0.6528364858807157,
1886
+ "eval_runtime": 15.5766,
1887
+ "eval_samples_per_second": 0.642,
1888
+ "eval_steps_per_second": 0.321,
1889
+ "step": 18800
1890
+ },
1891
+ {
1892
+ "epoch": 2.16,
1893
+ "grad_norm": 0.39267703890800476,
1894
+ "learning_rate": 9.178796251459824e-05,
1895
+ "loss": 1.4123,
1896
+ "step": 19000
1897
+ },
1898
+ {
1899
+ "epoch": 2.16,
1900
+ "eval_bertscore": 0.7298994064331055,
1901
+ "eval_loss": 1.7668545246124268,
1902
+ "eval_rouge1": 0.6490850022857569,
1903
+ "eval_rouge2": 0.3532323419511264,
1904
+ "eval_rougeL": 0.5212823000193295,
1905
+ "eval_rougeLsum": 0.636442724466695,
1906
+ "eval_runtime": 14.9094,
1907
+ "eval_samples_per_second": 0.671,
1908
+ "eval_steps_per_second": 0.335,
1909
+ "step": 19000
1910
+ },
1911
+ {
1912
+ "epoch": 2.19,
1913
+ "grad_norm": 0.38221287727355957,
1914
+ "learning_rate": 9.0648588600564e-05,
1915
+ "loss": 1.401,
1916
+ "step": 19200
1917
+ },
1918
+ {
1919
+ "epoch": 2.19,
1920
+ "eval_bertscore": 0.7316875457763672,
1921
+ "eval_loss": 1.764147400856018,
1922
+ "eval_rouge1": 0.6490326710625849,
1923
+ "eval_rouge2": 0.3510351037900723,
1924
+ "eval_rougeL": 0.5239165028795836,
1925
+ "eval_rougeLsum": 0.6373687316421427,
1926
+ "eval_runtime": 15.1192,
1927
+ "eval_samples_per_second": 0.661,
1928
+ "eval_steps_per_second": 0.331,
1929
+ "step": 19200
1930
+ },
1931
+ {
1932
+ "epoch": 2.21,
1933
+ "grad_norm": 0.3653150200843811,
1934
+ "learning_rate": 8.950921468652976e-05,
1935
+ "loss": 1.4109,
1936
+ "step": 19400
1937
+ },
1938
+ {
1939
+ "epoch": 2.21,
1940
+ "eval_bertscore": 0.7348155975341797,
1941
+ "eval_loss": 1.7640550136566162,
1942
+ "eval_rouge1": 0.6462152873276823,
1943
+ "eval_rouge2": 0.3483599145461069,
1944
+ "eval_rougeL": 0.5193372430687719,
1945
+ "eval_rougeLsum": 0.6334254357511564,
1946
+ "eval_runtime": 14.9291,
1947
+ "eval_samples_per_second": 0.67,
1948
+ "eval_steps_per_second": 0.335,
1949
+ "step": 19400
1950
+ },
1951
+ {
1952
+ "epoch": 2.23,
1953
+ "grad_norm": 0.38049009442329407,
1954
+ "learning_rate": 8.836984077249551e-05,
1955
+ "loss": 1.4189,
1956
+ "step": 19600
1957
+ },
1958
+ {
1959
+ "epoch": 2.23,
1960
+ "eval_bertscore": 0.7357938885688782,
1961
+ "eval_loss": 1.7696326971054077,
1962
+ "eval_rouge1": 0.6377276221057538,
1963
+ "eval_rouge2": 0.3455397190390045,
1964
+ "eval_rougeL": 0.5118069428064842,
1965
+ "eval_rougeLsum": 0.6264501633078481,
1966
+ "eval_runtime": 14.8653,
1967
+ "eval_samples_per_second": 0.673,
1968
+ "eval_steps_per_second": 0.336,
1969
+ "step": 19600
1970
+ },
1971
+ {
1972
+ "epoch": 2.26,
1973
+ "grad_norm": 0.42111098766326904,
1974
+ "learning_rate": 8.723046685846128e-05,
1975
+ "loss": 1.4152,
1976
+ "step": 19800
1977
+ },
1978
+ {
1979
+ "epoch": 2.26,
1980
+ "eval_bertscore": 0.7339056134223938,
1981
+ "eval_loss": 1.7658218145370483,
1982
+ "eval_rouge1": 0.6494820372695989,
1983
+ "eval_rouge2": 0.34691658128805236,
1984
+ "eval_rougeL": 0.5193228965163086,
1985
+ "eval_rougeLsum": 0.6365347065687565,
1986
+ "eval_runtime": 15.3562,
1987
+ "eval_samples_per_second": 0.651,
1988
+ "eval_steps_per_second": 0.326,
1989
+ "step": 19800
1990
+ },
1991
+ {
1992
+ "epoch": 2.28,
1993
+ "grad_norm": 0.4452258050441742,
1994
+ "learning_rate": 8.609109294442704e-05,
1995
+ "loss": 1.4101,
1996
+ "step": 20000
1997
+ },
1998
+ {
1999
+ "epoch": 2.28,
2000
+ "eval_bertscore": 0.7296434640884399,
2001
+ "eval_loss": 1.7714240550994873,
2002
+ "eval_rouge1": 0.6565600824405751,
2003
+ "eval_rouge2": 0.3533618655201594,
2004
+ "eval_rougeL": 0.5263318202066467,
2005
+ "eval_rougeLsum": 0.6444964824298407,
2006
+ "eval_runtime": 14.8578,
2007
+ "eval_samples_per_second": 0.673,
2008
+ "eval_steps_per_second": 0.337,
2009
+ "step": 20000
2010
+ },
2011
+ {
2012
+ "epoch": 2.3,
2013
+ "grad_norm": 0.4030967652797699,
2014
+ "learning_rate": 8.495171903039281e-05,
2015
+ "loss": 1.4049,
2016
+ "step": 20200
2017
+ },
2018
+ {
2019
+ "epoch": 2.3,
2020
+ "eval_bertscore": 0.7307097315788269,
2021
+ "eval_loss": 1.774444580078125,
2022
+ "eval_rouge1": 0.6517204836155526,
2023
+ "eval_rouge2": 0.3521339653276223,
2024
+ "eval_rougeL": 0.5223211728244184,
2025
+ "eval_rougeLsum": 0.6398710531932736,
2026
+ "eval_runtime": 15.8543,
2027
+ "eval_samples_per_second": 0.631,
2028
+ "eval_steps_per_second": 0.315,
2029
+ "step": 20200
2030
+ },
2031
+ {
2032
+ "epoch": 2.32,
2033
+ "grad_norm": 0.33409813046455383,
2034
+ "learning_rate": 8.381234511635858e-05,
2035
+ "loss": 1.4243,
2036
+ "step": 20400
2037
+ },
2038
+ {
2039
+ "epoch": 2.32,
2040
+ "eval_bertscore": 0.7312101721763611,
2041
+ "eval_loss": 1.7654094696044922,
2042
+ "eval_rouge1": 0.6607249126293291,
2043
+ "eval_rouge2": 0.3545993249716188,
2044
+ "eval_rougeL": 0.5320161007986739,
2045
+ "eval_rougeLsum": 0.6503315335963733,
2046
+ "eval_runtime": 14.8739,
2047
+ "eval_samples_per_second": 0.672,
2048
+ "eval_steps_per_second": 0.336,
2049
+ "step": 20400
2050
+ },
2051
+ {
2052
+ "epoch": 2.35,
2053
+ "grad_norm": 0.4044789671897888,
2054
+ "learning_rate": 8.267297120232433e-05,
2055
+ "loss": 1.413,
2056
+ "step": 20600
2057
+ },
2058
+ {
2059
+ "epoch": 2.35,
2060
+ "eval_bertscore": 0.7342169880867004,
2061
+ "eval_loss": 1.769879937171936,
2062
+ "eval_rouge1": 0.6442777880355144,
2063
+ "eval_rouge2": 0.35006080708477183,
2064
+ "eval_rougeL": 0.5218799478770955,
2065
+ "eval_rougeLsum": 0.6332700294558067,
2066
+ "eval_runtime": 14.9089,
2067
+ "eval_samples_per_second": 0.671,
2068
+ "eval_steps_per_second": 0.335,
2069
+ "step": 20600
2070
+ },
2071
+ {
2072
+ "epoch": 2.37,
2073
+ "grad_norm": 0.39801183342933655,
2074
+ "learning_rate": 8.153359728829008e-05,
2075
+ "loss": 1.4177,
2076
+ "step": 20800
2077
+ },
2078
+ {
2079
+ "epoch": 2.37,
2080
+ "eval_bertscore": 0.7343758344650269,
2081
+ "eval_loss": 1.7737929821014404,
2082
+ "eval_rouge1": 0.6495678172205896,
2083
+ "eval_rouge2": 0.3505195734345703,
2084
+ "eval_rougeL": 0.5263025592812188,
2085
+ "eval_rougeLsum": 0.6390057749428748,
2086
+ "eval_runtime": 15.2148,
2087
+ "eval_samples_per_second": 0.657,
2088
+ "eval_steps_per_second": 0.329,
2089
+ "step": 20800
2090
+ }
2091
+ ],
2092
+ "logging_steps": 200,
2093
+ "max_steps": 35112,
2094
+ "num_input_tokens_seen": 0,
2095
+ "num_train_epochs": 4,
2096
+ "save_steps": 800,
2097
+ "total_flos": 2.1077602489057567e+18,
2098
+ "train_batch_size": 2,
2099
+ "trial_name": null,
2100
+ "trial_params": null
2101
+ }
checkpoint-20800/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d576743d4294cfbcae212243377437f73cabbcded2df9da7f73e6e39ecb38f56
3
+ size 5048
checkpoint-21600/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: peft
3
+ base_model: unsloth/gemma-2b-bnb-4bit
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.10.0
checkpoint-21600/adapter_config.json ADDED
@@ -0,0 +1,34 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "unsloth/gemma-2b-bnb-4bit",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 32,
14
+ "lora_dropout": 0,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 64,
20
+ "rank_pattern": {},
21
+ "revision": "unsloth",
22
+ "target_modules": [
23
+ "v_proj",
24
+ "up_proj",
25
+ "gate_proj",
26
+ "o_proj",
27
+ "k_proj",
28
+ "down_proj",
29
+ "q_proj"
30
+ ],
31
+ "task_type": "CAUSAL_LM",
32
+ "use_dora": false,
33
+ "use_rslora": false
34
+ }
checkpoint-21600/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:5a9fcd274c0981e09f7a56fc7df572e5f0b95bc58848f8bf7531f5054e18c99c
3
+ size 313820248
checkpoint-21600/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:6a56b97f12072d267caf15b1f0d1101714ba6380a7c60c5a83e68808dc36d773
3
+ size 14244
checkpoint-21600/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a4ca451b22b6741c0b9a90d4a0705be6a2e71a2b099ab0a034a9a7bd72141ef9
3
+ size 1064
checkpoint-21600/special_tokens_map.json ADDED
@@ -0,0 +1,34 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "additional_special_tokens": [
3
+ "<start_of_turn>",
4
+ "<end_of_turn>"
5
+ ],
6
+ "bos_token": {
7
+ "content": "<bos>",
8
+ "lstrip": false,
9
+ "normalized": false,
10
+ "rstrip": false,
11
+ "single_word": false
12
+ },
13
+ "eos_token": {
14
+ "content": "<eos>",
15
+ "lstrip": false,
16
+ "normalized": false,
17
+ "rstrip": false,
18
+ "single_word": false
19
+ },
20
+ "pad_token": {
21
+ "content": "<pad>",
22
+ "lstrip": false,
23
+ "normalized": false,
24
+ "rstrip": false,
25
+ "single_word": false
26
+ },
27
+ "unk_token": {
28
+ "content": "<unk>",
29
+ "lstrip": false,
30
+ "normalized": false,
31
+ "rstrip": false,
32
+ "single_word": false
33
+ }
34
+ }
checkpoint-21600/tokenizer.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:05e97791a5e007260de1db7e1692e53150e08cea481e2bf25435553380c147ee
3
+ size 17477929
checkpoint-21600/tokenizer.model ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:61a7b147390c64585d6c3543dd6fc636906c9af3865a5548f27f31aee1d4c8e2
3
+ size 4241003
checkpoint-21600/tokenizer_config.json ADDED
@@ -0,0 +1,71 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_bos_token": true,
3
+ "add_eos_token": false,
4
+ "added_tokens_decoder": {
5
+ "0": {
6
+ "content": "<pad>",
7
+ "lstrip": false,
8
+ "normalized": false,
9
+ "rstrip": false,
10
+ "single_word": false,
11
+ "special": true
12
+ },
13
+ "1": {
14
+ "content": "<eos>",
15
+ "lstrip": false,
16
+ "normalized": false,
17
+ "rstrip": false,
18
+ "single_word": false,
19
+ "special": true
20
+ },
21
+ "2": {
22
+ "content": "<bos>",
23
+ "lstrip": false,
24
+ "normalized": false,
25
+ "rstrip": false,
26
+ "single_word": false,
27
+ "special": true
28
+ },
29
+ "3": {
30
+ "content": "<unk>",
31
+ "lstrip": false,
32
+ "normalized": false,
33
+ "rstrip": false,
34
+ "single_word": false,
35
+ "special": true
36
+ },
37
+ "106": {
38
+ "content": "<start_of_turn>",
39
+ "lstrip": false,
40
+ "normalized": false,
41
+ "rstrip": false,
42
+ "single_word": false,
43
+ "special": true
44
+ },
45
+ "107": {
46
+ "content": "<end_of_turn>",
47
+ "lstrip": false,
48
+ "normalized": false,
49
+ "rstrip": false,
50
+ "single_word": false,
51
+ "special": true
52
+ }
53
+ },
54
+ "additional_special_tokens": [
55
+ "<start_of_turn>",
56
+ "<end_of_turn>"
57
+ ],
58
+ "bos_token": "<bos>",
59
+ "chat_template": "{{ bos_token }}{% if messages[0]['role'] == 'system' %}{{ raise_exception('System role not supported') }}{% endif %}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if (message['role'] == 'assistant') %}{% set role = 'model' %}{% else %}{% set role = message['role'] %}{% endif %}{{ '<start_of_turn>' + role + '\n' + message['content'] | trim + '<end_of_turn>\n' }}{% endfor %}{% if add_generation_prompt %}{{'<start_of_turn>model\n'}}{% endif %}",
60
+ "clean_up_tokenization_spaces": false,
61
+ "eos_token": "<eos>",
62
+ "legacy": null,
63
+ "model_max_length": 8192,
64
+ "pad_token": "<pad>",
65
+ "padding_side": "right",
66
+ "sp_model_kwargs": {},
67
+ "spaces_between_special_tokens": false,
68
+ "tokenizer_class": "GemmaTokenizer",
69
+ "unk_token": "<unk>",
70
+ "use_default_system_prompt": false
71
+ }
checkpoint-21600/trainer_state.json ADDED
@@ -0,0 +1,2181 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": null,
3
+ "best_model_checkpoint": null,
4
+ "epoch": 2.4605570427749615,
5
+ "eval_steps": 200,
6
+ "global_step": 21600,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.02,
13
+ "grad_norm": 0.1643640249967575,
14
+ "learning_rate": 0.0001988891104338166,
15
+ "loss": 1.7673,
16
+ "step": 200
17
+ },
18
+ {
19
+ "epoch": 0.02,
20
+ "eval_bertscore": 0.7312520742416382,
21
+ "eval_loss": 1.7944419384002686,
22
+ "eval_rouge1": 0.645726048132668,
23
+ "eval_rouge2": 0.342840307585653,
24
+ "eval_rougeL": 0.5174784271125388,
25
+ "eval_rougeLsum": 0.6359911842715976,
26
+ "eval_runtime": 67.7968,
27
+ "eval_samples_per_second": 0.147,
28
+ "eval_steps_per_second": 0.074,
29
+ "step": 200
30
+ },
31
+ {
32
+ "epoch": 0.05,
33
+ "grad_norm": 0.17238478362560272,
34
+ "learning_rate": 0.00019774973651978238,
35
+ "loss": 1.6985,
36
+ "step": 400
37
+ },
38
+ {
39
+ "epoch": 0.05,
40
+ "eval_bertscore": 0.733666718006134,
41
+ "eval_loss": 1.7791178226470947,
42
+ "eval_rouge1": 0.6540909153028596,
43
+ "eval_rouge2": 0.3548819059818129,
44
+ "eval_rougeL": 0.527257232694246,
45
+ "eval_rougeLsum": 0.6442799950994005,
46
+ "eval_runtime": 15.1267,
47
+ "eval_samples_per_second": 0.661,
48
+ "eval_steps_per_second": 0.331,
49
+ "step": 400
50
+ },
51
+ {
52
+ "epoch": 0.07,
53
+ "grad_norm": 0.19368696212768555,
54
+ "learning_rate": 0.00019661036260574814,
55
+ "loss": 1.6962,
56
+ "step": 600
57
+ },
58
+ {
59
+ "epoch": 0.07,
60
+ "eval_bertscore": 0.7339462041854858,
61
+ "eval_loss": 1.7609882354736328,
62
+ "eval_rouge1": 0.6384337329686338,
63
+ "eval_rouge2": 0.3415514270662107,
64
+ "eval_rougeL": 0.51206080148464,
65
+ "eval_rougeLsum": 0.6261968614666548,
66
+ "eval_runtime": 15.2068,
67
+ "eval_samples_per_second": 0.658,
68
+ "eval_steps_per_second": 0.329,
69
+ "step": 600
70
+ },
71
+ {
72
+ "epoch": 0.09,
73
+ "grad_norm": 0.18629203736782074,
74
+ "learning_rate": 0.00019547098869171392,
75
+ "loss": 1.6825,
76
+ "step": 800
77
+ },
78
+ {
79
+ "epoch": 0.09,
80
+ "eval_bertscore": 0.7363594174385071,
81
+ "eval_loss": 1.7610784769058228,
82
+ "eval_rouge1": 0.6461624591922237,
83
+ "eval_rouge2": 0.3477371388439609,
84
+ "eval_rougeL": 0.5187429174752844,
85
+ "eval_rougeLsum": 0.6361089823008282,
86
+ "eval_runtime": 15.173,
87
+ "eval_samples_per_second": 0.659,
88
+ "eval_steps_per_second": 0.33,
89
+ "step": 800
90
+ },
91
+ {
92
+ "epoch": 0.11,
93
+ "grad_norm": 0.1799013316631317,
94
+ "learning_rate": 0.00019433161477767967,
95
+ "loss": 1.6848,
96
+ "step": 1000
97
+ },
98
+ {
99
+ "epoch": 0.11,
100
+ "eval_bertscore": 0.7334067225456238,
101
+ "eval_loss": 1.7576347589492798,
102
+ "eval_rouge1": 0.6345119236349537,
103
+ "eval_rouge2": 0.3422519149071803,
104
+ "eval_rougeL": 0.5111983101326238,
105
+ "eval_rougeLsum": 0.6244653120436832,
106
+ "eval_runtime": 15.2847,
107
+ "eval_samples_per_second": 0.654,
108
+ "eval_steps_per_second": 0.327,
109
+ "step": 1000
110
+ },
111
+ {
112
+ "epoch": 0.14,
113
+ "grad_norm": 0.22036150097846985,
114
+ "learning_rate": 0.00019319224086364545,
115
+ "loss": 1.6714,
116
+ "step": 1200
117
+ },
118
+ {
119
+ "epoch": 0.14,
120
+ "eval_bertscore": 0.7323788404464722,
121
+ "eval_loss": 1.7521806955337524,
122
+ "eval_rouge1": 0.6452540184557478,
123
+ "eval_rouge2": 0.3465145726476423,
124
+ "eval_rougeL": 0.516711757588783,
125
+ "eval_rougeLsum": 0.6341049885677059,
126
+ "eval_runtime": 15.1247,
127
+ "eval_samples_per_second": 0.661,
128
+ "eval_steps_per_second": 0.331,
129
+ "step": 1200
130
+ },
131
+ {
132
+ "epoch": 0.16,
133
+ "grad_norm": 0.21381086111068726,
134
+ "learning_rate": 0.0001920528669496112,
135
+ "loss": 1.6669,
136
+ "step": 1400
137
+ },
138
+ {
139
+ "epoch": 0.16,
140
+ "eval_bertscore": 0.7313202619552612,
141
+ "eval_loss": 1.7520482540130615,
142
+ "eval_rouge1": 0.6397526546254797,
143
+ "eval_rouge2": 0.3452671288110514,
144
+ "eval_rougeL": 0.5176580626678706,
145
+ "eval_rougeLsum": 0.6296746647539768,
146
+ "eval_runtime": 15.183,
147
+ "eval_samples_per_second": 0.659,
148
+ "eval_steps_per_second": 0.329,
149
+ "step": 1400
150
+ },
151
+ {
152
+ "epoch": 0.18,
153
+ "grad_norm": 0.20332874357700348,
154
+ "learning_rate": 0.00019091349303557696,
155
+ "loss": 1.671,
156
+ "step": 1600
157
+ },
158
+ {
159
+ "epoch": 0.18,
160
+ "eval_bertscore": 0.7349230647087097,
161
+ "eval_loss": 1.7473630905151367,
162
+ "eval_rouge1": 0.637439872504459,
163
+ "eval_rouge2": 0.34307164454056094,
164
+ "eval_rougeL": 0.5129717676228565,
165
+ "eval_rougeLsum": 0.6272190896182391,
166
+ "eval_runtime": 15.5672,
167
+ "eval_samples_per_second": 0.642,
168
+ "eval_steps_per_second": 0.321,
169
+ "step": 1600
170
+ },
171
+ {
172
+ "epoch": 0.21,
173
+ "grad_norm": 0.2025599479675293,
174
+ "learning_rate": 0.00018977411912154274,
175
+ "loss": 1.6721,
176
+ "step": 1800
177
+ },
178
+ {
179
+ "epoch": 0.21,
180
+ "eval_bertscore": 0.7357184290885925,
181
+ "eval_loss": 1.7516342401504517,
182
+ "eval_rouge1": 0.6387615819926658,
183
+ "eval_rouge2": 0.34366787517105574,
184
+ "eval_rougeL": 0.5129026911770751,
185
+ "eval_rougeLsum": 0.6289314118258257,
186
+ "eval_runtime": 15.9574,
187
+ "eval_samples_per_second": 0.627,
188
+ "eval_steps_per_second": 0.313,
189
+ "step": 1800
190
+ },
191
+ {
192
+ "epoch": 0.23,
193
+ "grad_norm": 0.20457112789154053,
194
+ "learning_rate": 0.0001886347452075085,
195
+ "loss": 1.671,
196
+ "step": 2000
197
+ },
198
+ {
199
+ "epoch": 0.23,
200
+ "eval_bertscore": 0.733718752861023,
201
+ "eval_loss": 1.7501707077026367,
202
+ "eval_rouge1": 0.6346207681220664,
203
+ "eval_rouge2": 0.33748369437614106,
204
+ "eval_rougeL": 0.5085159047705141,
205
+ "eval_rougeLsum": 0.6239953154441167,
206
+ "eval_runtime": 15.0863,
207
+ "eval_samples_per_second": 0.663,
208
+ "eval_steps_per_second": 0.331,
209
+ "step": 2000
210
+ },
211
+ {
212
+ "epoch": 0.25,
213
+ "grad_norm": 0.22552740573883057,
214
+ "learning_rate": 0.00018749537129347424,
215
+ "loss": 1.6496,
216
+ "step": 2200
217
+ },
218
+ {
219
+ "epoch": 0.25,
220
+ "eval_bertscore": 0.7368552684783936,
221
+ "eval_loss": 1.7437107563018799,
222
+ "eval_rouge1": 0.6490756387878311,
223
+ "eval_rouge2": 0.3448817738175175,
224
+ "eval_rougeL": 0.5235187045706321,
225
+ "eval_rougeLsum": 0.6377780857890332,
226
+ "eval_runtime": 15.07,
227
+ "eval_samples_per_second": 0.664,
228
+ "eval_steps_per_second": 0.332,
229
+ "step": 2200
230
+ },
231
+ {
232
+ "epoch": 0.27,
233
+ "grad_norm": 0.22573673725128174,
234
+ "learning_rate": 0.00018635599737944,
235
+ "loss": 1.6629,
236
+ "step": 2400
237
+ },
238
+ {
239
+ "epoch": 0.27,
240
+ "eval_bertscore": 0.7314499616622925,
241
+ "eval_loss": 1.7462828159332275,
242
+ "eval_rouge1": 0.6511482369678803,
243
+ "eval_rouge2": 0.34632544827771805,
244
+ "eval_rougeL": 0.5212417191003778,
245
+ "eval_rougeLsum": 0.6415391907940229,
246
+ "eval_runtime": 15.2078,
247
+ "eval_samples_per_second": 0.658,
248
+ "eval_steps_per_second": 0.329,
249
+ "step": 2400
250
+ },
251
+ {
252
+ "epoch": 0.3,
253
+ "grad_norm": 0.26426687836647034,
254
+ "learning_rate": 0.00018521662346540575,
255
+ "loss": 1.6644,
256
+ "step": 2600
257
+ },
258
+ {
259
+ "epoch": 0.3,
260
+ "eval_bertscore": 0.7363359928131104,
261
+ "eval_loss": 1.7505037784576416,
262
+ "eval_rouge1": 0.6498296552335481,
263
+ "eval_rouge2": 0.34873833589761183,
264
+ "eval_rougeL": 0.5194028620820592,
265
+ "eval_rougeLsum": 0.6404603087578984,
266
+ "eval_runtime": 14.8403,
267
+ "eval_samples_per_second": 0.674,
268
+ "eval_steps_per_second": 0.337,
269
+ "step": 2600
270
+ },
271
+ {
272
+ "epoch": 0.32,
273
+ "grad_norm": 0.20142091810703278,
274
+ "learning_rate": 0.00018407724955137153,
275
+ "loss": 1.6535,
276
+ "step": 2800
277
+ },
278
+ {
279
+ "epoch": 0.32,
280
+ "eval_bertscore": 0.7304679155349731,
281
+ "eval_loss": 1.7511039972305298,
282
+ "eval_rouge1": 0.6475130585388738,
283
+ "eval_rouge2": 0.34648331046897884,
284
+ "eval_rougeL": 0.5218042284020985,
285
+ "eval_rougeLsum": 0.6382749834402862,
286
+ "eval_runtime": 15.0162,
287
+ "eval_samples_per_second": 0.666,
288
+ "eval_steps_per_second": 0.333,
289
+ "step": 2800
290
+ },
291
+ {
292
+ "epoch": 0.34,
293
+ "grad_norm": 0.23283220827579498,
294
+ "learning_rate": 0.00018293787563733728,
295
+ "loss": 1.6477,
296
+ "step": 3000
297
+ },
298
+ {
299
+ "epoch": 0.34,
300
+ "eval_bertscore": 0.7327049374580383,
301
+ "eval_loss": 1.7461665868759155,
302
+ "eval_rouge1": 0.6309349586871908,
303
+ "eval_rouge2": 0.3387882478990309,
304
+ "eval_rougeL": 0.5042059192403674,
305
+ "eval_rougeLsum": 0.6210432469674847,
306
+ "eval_runtime": 15.463,
307
+ "eval_samples_per_second": 0.647,
308
+ "eval_steps_per_second": 0.323,
309
+ "step": 3000
310
+ },
311
+ {
312
+ "epoch": 0.36,
313
+ "grad_norm": 0.21316750347614288,
314
+ "learning_rate": 0.00018179850172330306,
315
+ "loss": 1.6614,
316
+ "step": 3200
317
+ },
318
+ {
319
+ "epoch": 0.36,
320
+ "eval_bertscore": 0.7314620018005371,
321
+ "eval_loss": 1.7468239068984985,
322
+ "eval_rouge1": 0.6480904534152265,
323
+ "eval_rouge2": 0.3479530168963481,
324
+ "eval_rougeL": 0.5193148273848067,
325
+ "eval_rougeLsum": 0.6366010767207634,
326
+ "eval_runtime": 15.0381,
327
+ "eval_samples_per_second": 0.665,
328
+ "eval_steps_per_second": 0.332,
329
+ "step": 3200
330
+ },
331
+ {
332
+ "epoch": 0.39,
333
+ "grad_norm": 0.26080408692359924,
334
+ "learning_rate": 0.00018065912780926882,
335
+ "loss": 1.6591,
336
+ "step": 3400
337
+ },
338
+ {
339
+ "epoch": 0.39,
340
+ "eval_bertscore": 0.7327477335929871,
341
+ "eval_loss": 1.7442594766616821,
342
+ "eval_rouge1": 0.6424613378037144,
343
+ "eval_rouge2": 0.34731770322974903,
344
+ "eval_rougeL": 0.5160705879794565,
345
+ "eval_rougeLsum": 0.6327006420281607,
346
+ "eval_runtime": 15.5373,
347
+ "eval_samples_per_second": 0.644,
348
+ "eval_steps_per_second": 0.322,
349
+ "step": 3400
350
+ },
351
+ {
352
+ "epoch": 0.41,
353
+ "grad_norm": 0.23274216055870056,
354
+ "learning_rate": 0.0001795197538952346,
355
+ "loss": 1.6613,
356
+ "step": 3600
357
+ },
358
+ {
359
+ "epoch": 0.41,
360
+ "eval_bertscore": 0.736956000328064,
361
+ "eval_loss": 1.7429373264312744,
362
+ "eval_rouge1": 0.6514574160666677,
363
+ "eval_rouge2": 0.3556199242231646,
364
+ "eval_rougeL": 0.5249726237675663,
365
+ "eval_rougeLsum": 0.6406261097623661,
366
+ "eval_runtime": 14.9415,
367
+ "eval_samples_per_second": 0.669,
368
+ "eval_steps_per_second": 0.335,
369
+ "step": 3600
370
+ },
371
+ {
372
+ "epoch": 0.43,
373
+ "grad_norm": 0.23616766929626465,
374
+ "learning_rate": 0.00017838037998120035,
375
+ "loss": 1.6479,
376
+ "step": 3800
377
+ },
378
+ {
379
+ "epoch": 0.43,
380
+ "eval_bertscore": 0.7349627614021301,
381
+ "eval_loss": 1.7420669794082642,
382
+ "eval_rouge1": 0.655851684949526,
383
+ "eval_rouge2": 0.35254590691865084,
384
+ "eval_rougeL": 0.5248980956621441,
385
+ "eval_rougeLsum": 0.6449637270581419,
386
+ "eval_runtime": 15.4178,
387
+ "eval_samples_per_second": 0.649,
388
+ "eval_steps_per_second": 0.324,
389
+ "step": 3800
390
+ },
391
+ {
392
+ "epoch": 0.46,
393
+ "grad_norm": 0.23260319232940674,
394
+ "learning_rate": 0.0001772410060671661,
395
+ "loss": 1.6569,
396
+ "step": 4000
397
+ },
398
+ {
399
+ "epoch": 0.46,
400
+ "eval_bertscore": 0.7332885265350342,
401
+ "eval_loss": 1.7401313781738281,
402
+ "eval_rouge1": 0.6669483634140105,
403
+ "eval_rouge2": 0.35873988835161297,
404
+ "eval_rougeL": 0.5343868725007427,
405
+ "eval_rougeLsum": 0.6555353134690931,
406
+ "eval_runtime": 15.0822,
407
+ "eval_samples_per_second": 0.663,
408
+ "eval_steps_per_second": 0.332,
409
+ "step": 4000
410
+ },
411
+ {
412
+ "epoch": 0.48,
413
+ "grad_norm": 0.2366473525762558,
414
+ "learning_rate": 0.00017610163215313186,
415
+ "loss": 1.6599,
416
+ "step": 4200
417
+ },
418
+ {
419
+ "epoch": 0.48,
420
+ "eval_bertscore": 0.7335314750671387,
421
+ "eval_loss": 1.7385823726654053,
422
+ "eval_rouge1": 0.6559297063578133,
423
+ "eval_rouge2": 0.35483499789990636,
424
+ "eval_rougeL": 0.5297939800986089,
425
+ "eval_rougeLsum": 0.6454544372491222,
426
+ "eval_runtime": 15.1029,
427
+ "eval_samples_per_second": 0.662,
428
+ "eval_steps_per_second": 0.331,
429
+ "step": 4200
430
+ },
431
+ {
432
+ "epoch": 0.5,
433
+ "grad_norm": 0.20628753304481506,
434
+ "learning_rate": 0.0001749622582390976,
435
+ "loss": 1.6454,
436
+ "step": 4400
437
+ },
438
+ {
439
+ "epoch": 0.5,
440
+ "eval_bertscore": 0.7342795133590698,
441
+ "eval_loss": 1.7422058582305908,
442
+ "eval_rouge1": 0.660746519614568,
443
+ "eval_rouge2": 0.3633965895561597,
444
+ "eval_rougeL": 0.5369036980876734,
445
+ "eval_rougeLsum": 0.650338328328998,
446
+ "eval_runtime": 15.4434,
447
+ "eval_samples_per_second": 0.648,
448
+ "eval_steps_per_second": 0.324,
449
+ "step": 4400
450
+ },
451
+ {
452
+ "epoch": 0.52,
453
+ "grad_norm": 0.2239149957895279,
454
+ "learning_rate": 0.0001738228843250634,
455
+ "loss": 1.6594,
456
+ "step": 4600
457
+ },
458
+ {
459
+ "epoch": 0.52,
460
+ "eval_bertscore": 0.7313543558120728,
461
+ "eval_loss": 1.740854263305664,
462
+ "eval_rouge1": 0.6591645132619427,
463
+ "eval_rouge2": 0.35766117432431743,
464
+ "eval_rougeL": 0.532710255034635,
465
+ "eval_rougeLsum": 0.6479428185884644,
466
+ "eval_runtime": 14.9436,
467
+ "eval_samples_per_second": 0.669,
468
+ "eval_steps_per_second": 0.335,
469
+ "step": 4600
470
+ },
471
+ {
472
+ "epoch": 0.55,
473
+ "grad_norm": 0.24808338284492493,
474
+ "learning_rate": 0.00017268351041102914,
475
+ "loss": 1.6604,
476
+ "step": 4800
477
+ },
478
+ {
479
+ "epoch": 0.55,
480
+ "eval_bertscore": 0.7333321571350098,
481
+ "eval_loss": 1.7385585308074951,
482
+ "eval_rouge1": 0.6532115808232871,
483
+ "eval_rouge2": 0.35333788022501567,
484
+ "eval_rougeL": 0.5284071547874328,
485
+ "eval_rougeLsum": 0.6410472452797623,
486
+ "eval_runtime": 15.0277,
487
+ "eval_samples_per_second": 0.665,
488
+ "eval_steps_per_second": 0.333,
489
+ "step": 4800
490
+ },
491
+ {
492
+ "epoch": 0.57,
493
+ "grad_norm": 0.2555364966392517,
494
+ "learning_rate": 0.0001715441364969949,
495
+ "loss": 1.6493,
496
+ "step": 5000
497
+ },
498
+ {
499
+ "epoch": 0.57,
500
+ "eval_bertscore": 0.7318152189254761,
501
+ "eval_loss": 1.7357494831085205,
502
+ "eval_rouge1": 0.6476755890502586,
503
+ "eval_rouge2": 0.35312778275949164,
504
+ "eval_rougeL": 0.5227601228049905,
505
+ "eval_rougeLsum": 0.6371331138372852,
506
+ "eval_runtime": 14.8807,
507
+ "eval_samples_per_second": 0.672,
508
+ "eval_steps_per_second": 0.336,
509
+ "step": 5000
510
+ },
511
+ {
512
+ "epoch": 0.59,
513
+ "grad_norm": 0.21518155932426453,
514
+ "learning_rate": 0.00017040476258296068,
515
+ "loss": 1.644,
516
+ "step": 5200
517
+ },
518
+ {
519
+ "epoch": 0.59,
520
+ "eval_bertscore": 0.734805703163147,
521
+ "eval_loss": 1.74032723903656,
522
+ "eval_rouge1": 0.6476813733451636,
523
+ "eval_rouge2": 0.3509259728617576,
524
+ "eval_rougeL": 0.5221334872800274,
525
+ "eval_rougeLsum": 0.636892384667733,
526
+ "eval_runtime": 15.1271,
527
+ "eval_samples_per_second": 0.661,
528
+ "eval_steps_per_second": 0.331,
529
+ "step": 5200
530
+ },
531
+ {
532
+ "epoch": 0.62,
533
+ "grad_norm": 0.26086658239364624,
534
+ "learning_rate": 0.00016926538866892643,
535
+ "loss": 1.6449,
536
+ "step": 5400
537
+ },
538
+ {
539
+ "epoch": 0.62,
540
+ "eval_bertscore": 0.7339995503425598,
541
+ "eval_loss": 1.7338205575942993,
542
+ "eval_rouge1": 0.6416889902864902,
543
+ "eval_rouge2": 0.3479045880347737,
544
+ "eval_rougeL": 0.5160577838468976,
545
+ "eval_rougeLsum": 0.6317983411796093,
546
+ "eval_runtime": 14.9992,
547
+ "eval_samples_per_second": 0.667,
548
+ "eval_steps_per_second": 0.333,
549
+ "step": 5400
550
+ },
551
+ {
552
+ "epoch": 0.64,
553
+ "grad_norm": 0.25449469685554504,
554
+ "learning_rate": 0.0001681260147548922,
555
+ "loss": 1.6299,
556
+ "step": 5600
557
+ },
558
+ {
559
+ "epoch": 0.64,
560
+ "eval_bertscore": 0.7306328415870667,
561
+ "eval_loss": 1.7369228601455688,
562
+ "eval_rouge1": 0.6390760905985684,
563
+ "eval_rouge2": 0.3409328272828699,
564
+ "eval_rougeL": 0.5111832543685331,
565
+ "eval_rougeLsum": 0.6285753423407665,
566
+ "eval_runtime": 15.483,
567
+ "eval_samples_per_second": 0.646,
568
+ "eval_steps_per_second": 0.323,
569
+ "step": 5600
570
+ },
571
+ {
572
+ "epoch": 0.66,
573
+ "grad_norm": 0.24706102907657623,
574
+ "learning_rate": 0.00016698664084085796,
575
+ "loss": 1.6374,
576
+ "step": 5800
577
+ },
578
+ {
579
+ "epoch": 0.66,
580
+ "eval_bertscore": 0.732075572013855,
581
+ "eval_loss": 1.7343876361846924,
582
+ "eval_rouge1": 0.6378821977913272,
583
+ "eval_rouge2": 0.34619427775171585,
584
+ "eval_rougeL": 0.5120186953041237,
585
+ "eval_rougeLsum": 0.6284056323839109,
586
+ "eval_runtime": 15.7341,
587
+ "eval_samples_per_second": 0.636,
588
+ "eval_steps_per_second": 0.318,
589
+ "step": 5800
590
+ },
591
+ {
592
+ "epoch": 0.68,
593
+ "grad_norm": 0.24373260140419006,
594
+ "learning_rate": 0.00016584726692682372,
595
+ "loss": 1.6427,
596
+ "step": 6000
597
+ },
598
+ {
599
+ "epoch": 0.68,
600
+ "eval_bertscore": 0.7350374460220337,
601
+ "eval_loss": 1.729591965675354,
602
+ "eval_rouge1": 0.6516545226356616,
603
+ "eval_rouge2": 0.35485762033878543,
604
+ "eval_rougeL": 0.5249054193354852,
605
+ "eval_rougeLsum": 0.6411016821651583,
606
+ "eval_runtime": 15.5199,
607
+ "eval_samples_per_second": 0.644,
608
+ "eval_steps_per_second": 0.322,
609
+ "step": 6000
610
+ },
611
+ {
612
+ "epoch": 0.71,
613
+ "grad_norm": 0.24616578221321106,
614
+ "learning_rate": 0.0001647078930127895,
615
+ "loss": 1.6296,
616
+ "step": 6200
617
+ },
618
+ {
619
+ "epoch": 0.71,
620
+ "eval_bertscore": 0.7335461378097534,
621
+ "eval_loss": 1.7302274703979492,
622
+ "eval_rouge1": 0.6531411706717427,
623
+ "eval_rouge2": 0.35003053174601517,
624
+ "eval_rougeL": 0.5212483686089053,
625
+ "eval_rougeLsum": 0.6438454124825417,
626
+ "eval_runtime": 15.3058,
627
+ "eval_samples_per_second": 0.653,
628
+ "eval_steps_per_second": 0.327,
629
+ "step": 6200
630
+ },
631
+ {
632
+ "epoch": 0.73,
633
+ "grad_norm": 0.24500492215156555,
634
+ "learning_rate": 0.00016356851909875522,
635
+ "loss": 1.6251,
636
+ "step": 6400
637
+ },
638
+ {
639
+ "epoch": 0.73,
640
+ "eval_bertscore": 0.7347471714019775,
641
+ "eval_loss": 1.7292228937149048,
642
+ "eval_rouge1": 0.6565322485502556,
643
+ "eval_rouge2": 0.35887540291607073,
644
+ "eval_rougeL": 0.5284326132878907,
645
+ "eval_rougeLsum": 0.6469750895866724,
646
+ "eval_runtime": 14.9708,
647
+ "eval_samples_per_second": 0.668,
648
+ "eval_steps_per_second": 0.334,
649
+ "step": 6400
650
+ },
651
+ {
652
+ "epoch": 0.75,
653
+ "grad_norm": 0.26575228571891785,
654
+ "learning_rate": 0.000162429145184721,
655
+ "loss": 1.6389,
656
+ "step": 6600
657
+ },
658
+ {
659
+ "epoch": 0.75,
660
+ "eval_bertscore": 0.7319897413253784,
661
+ "eval_loss": 1.7287580966949463,
662
+ "eval_rouge1": 0.6458608801881298,
663
+ "eval_rouge2": 0.3503480901452204,
664
+ "eval_rougeL": 0.519626708150005,
665
+ "eval_rougeLsum": 0.6362405734928169,
666
+ "eval_runtime": 15.3509,
667
+ "eval_samples_per_second": 0.651,
668
+ "eval_steps_per_second": 0.326,
669
+ "step": 6600
670
+ },
671
+ {
672
+ "epoch": 0.77,
673
+ "grad_norm": 0.27144965529441833,
674
+ "learning_rate": 0.00016128977127068676,
675
+ "loss": 1.6476,
676
+ "step": 6800
677
+ },
678
+ {
679
+ "epoch": 0.77,
680
+ "eval_bertscore": 0.7392772436141968,
681
+ "eval_loss": 1.7257907390594482,
682
+ "eval_rouge1": 0.6543238897579965,
683
+ "eval_rouge2": 0.3606726049451984,
684
+ "eval_rougeL": 0.5317585887753791,
685
+ "eval_rougeLsum": 0.6452028420624081,
686
+ "eval_runtime": 15.0268,
687
+ "eval_samples_per_second": 0.665,
688
+ "eval_steps_per_second": 0.333,
689
+ "step": 6800
690
+ },
691
+ {
692
+ "epoch": 0.8,
693
+ "grad_norm": 0.2579711079597473,
694
+ "learning_rate": 0.00016015039735665254,
695
+ "loss": 1.6316,
696
+ "step": 7000
697
+ },
698
+ {
699
+ "epoch": 0.8,
700
+ "eval_bertscore": 0.7375612854957581,
701
+ "eval_loss": 1.7296981811523438,
702
+ "eval_rouge1": 0.658906725408624,
703
+ "eval_rouge2": 0.35825094165644866,
704
+ "eval_rougeL": 0.5323299193377959,
705
+ "eval_rougeLsum": 0.6500364347290426,
706
+ "eval_runtime": 14.9244,
707
+ "eval_samples_per_second": 0.67,
708
+ "eval_steps_per_second": 0.335,
709
+ "step": 7000
710
+ },
711
+ {
712
+ "epoch": 0.82,
713
+ "grad_norm": 0.2589207589626312,
714
+ "learning_rate": 0.0001590110234426183,
715
+ "loss": 1.6432,
716
+ "step": 7200
717
+ },
718
+ {
719
+ "epoch": 0.82,
720
+ "eval_bertscore": 0.735145092010498,
721
+ "eval_loss": 1.72720205783844,
722
+ "eval_rouge1": 0.6678646250245518,
723
+ "eval_rouge2": 0.36332843150846983,
724
+ "eval_rougeL": 0.537576430733886,
725
+ "eval_rougeLsum": 0.6579789388660506,
726
+ "eval_runtime": 14.9067,
727
+ "eval_samples_per_second": 0.671,
728
+ "eval_steps_per_second": 0.335,
729
+ "step": 7200
730
+ },
731
+ {
732
+ "epoch": 0.84,
733
+ "grad_norm": 0.26652559638023376,
734
+ "learning_rate": 0.00015787164952858404,
735
+ "loss": 1.6488,
736
+ "step": 7400
737
+ },
738
+ {
739
+ "epoch": 0.84,
740
+ "eval_bertscore": 0.7320755124092102,
741
+ "eval_loss": 1.7282931804656982,
742
+ "eval_rouge1": 0.6325633297780734,
743
+ "eval_rouge2": 0.34505856555703185,
744
+ "eval_rougeL": 0.5100006743383693,
745
+ "eval_rougeLsum": 0.6230385336341938,
746
+ "eval_runtime": 14.9075,
747
+ "eval_samples_per_second": 0.671,
748
+ "eval_steps_per_second": 0.335,
749
+ "step": 7400
750
+ },
751
+ {
752
+ "epoch": 0.87,
753
+ "grad_norm": 0.27353721857070923,
754
+ "learning_rate": 0.00015673227561454982,
755
+ "loss": 1.6486,
756
+ "step": 7600
757
+ },
758
+ {
759
+ "epoch": 0.87,
760
+ "eval_bertscore": 0.7367390394210815,
761
+ "eval_loss": 1.7290785312652588,
762
+ "eval_rouge1": 0.639487116874423,
763
+ "eval_rouge2": 0.3466574229736927,
764
+ "eval_rougeL": 0.515038120249177,
765
+ "eval_rougeLsum": 0.6301157215372983,
766
+ "eval_runtime": 15.0876,
767
+ "eval_samples_per_second": 0.663,
768
+ "eval_steps_per_second": 0.331,
769
+ "step": 7600
770
+ },
771
+ {
772
+ "epoch": 0.89,
773
+ "grad_norm": 0.24777938425540924,
774
+ "learning_rate": 0.00015559290170051558,
775
+ "loss": 1.6271,
776
+ "step": 7800
777
+ },
778
+ {
779
+ "epoch": 0.89,
780
+ "eval_bertscore": 0.735866904258728,
781
+ "eval_loss": 1.7264015674591064,
782
+ "eval_rouge1": 0.64939597901302,
783
+ "eval_rouge2": 0.3554282813944538,
784
+ "eval_rougeL": 0.5247953329477759,
785
+ "eval_rougeLsum": 0.6405524812915908,
786
+ "eval_runtime": 14.8892,
787
+ "eval_samples_per_second": 0.672,
788
+ "eval_steps_per_second": 0.336,
789
+ "step": 7800
790
+ },
791
+ {
792
+ "epoch": 0.91,
793
+ "grad_norm": 0.2703794538974762,
794
+ "learning_rate": 0.00015445352778648136,
795
+ "loss": 1.6415,
796
+ "step": 8000
797
+ },
798
+ {
799
+ "epoch": 0.91,
800
+ "eval_bertscore": 0.7325771450996399,
801
+ "eval_loss": 1.7271970510482788,
802
+ "eval_rouge1": 0.6659432894288253,
803
+ "eval_rouge2": 0.35962933912652617,
804
+ "eval_rougeL": 0.5385420432813512,
805
+ "eval_rougeLsum": 0.6557027031484046,
806
+ "eval_runtime": 14.8319,
807
+ "eval_samples_per_second": 0.674,
808
+ "eval_steps_per_second": 0.337,
809
+ "step": 8000
810
+ },
811
+ {
812
+ "epoch": 0.93,
813
+ "grad_norm": 0.28753793239593506,
814
+ "learning_rate": 0.0001533141538724471,
815
+ "loss": 1.6239,
816
+ "step": 8200
817
+ },
818
+ {
819
+ "epoch": 0.93,
820
+ "eval_bertscore": 0.7350013852119446,
821
+ "eval_loss": 1.7266199588775635,
822
+ "eval_rouge1": 0.6549282561414593,
823
+ "eval_rouge2": 0.35694530595734475,
824
+ "eval_rougeL": 0.5301601006964574,
825
+ "eval_rougeLsum": 0.6441779306137909,
826
+ "eval_runtime": 14.9005,
827
+ "eval_samples_per_second": 0.671,
828
+ "eval_steps_per_second": 0.336,
829
+ "step": 8200
830
+ },
831
+ {
832
+ "epoch": 0.96,
833
+ "grad_norm": 0.23870150744915009,
834
+ "learning_rate": 0.00015217477995841286,
835
+ "loss": 1.6293,
836
+ "step": 8400
837
+ },
838
+ {
839
+ "epoch": 0.96,
840
+ "eval_bertscore": 0.7271261811256409,
841
+ "eval_loss": 1.7256368398666382,
842
+ "eval_rouge1": 0.6515513829901936,
843
+ "eval_rouge2": 0.35217616104918836,
844
+ "eval_rougeL": 0.5236553509227138,
845
+ "eval_rougeLsum": 0.6411473505324752,
846
+ "eval_runtime": 14.9938,
847
+ "eval_samples_per_second": 0.667,
848
+ "eval_steps_per_second": 0.333,
849
+ "step": 8400
850
+ },
851
+ {
852
+ "epoch": 0.98,
853
+ "grad_norm": 0.28276997804641724,
854
+ "learning_rate": 0.00015103540604437861,
855
+ "loss": 1.6242,
856
+ "step": 8600
857
+ },
858
+ {
859
+ "epoch": 0.98,
860
+ "eval_bertscore": 0.7347334027290344,
861
+ "eval_loss": 1.717627763748169,
862
+ "eval_rouge1": 0.6350112495847634,
863
+ "eval_rouge2": 0.3477570751550898,
864
+ "eval_rougeL": 0.5146616989899861,
865
+ "eval_rougeLsum": 0.6246669376525157,
866
+ "eval_runtime": 15.7032,
867
+ "eval_samples_per_second": 0.637,
868
+ "eval_steps_per_second": 0.318,
869
+ "step": 8600
870
+ },
871
+ {
872
+ "epoch": 1.0,
873
+ "grad_norm": 0.24915842711925507,
874
+ "learning_rate": 0.00014989603213034437,
875
+ "loss": 1.6245,
876
+ "step": 8800
877
+ },
878
+ {
879
+ "epoch": 1.0,
880
+ "eval_bertscore": 0.7313701510429382,
881
+ "eval_loss": 1.7292964458465576,
882
+ "eval_rouge1": 0.6479528105367669,
883
+ "eval_rouge2": 0.35020983244262877,
884
+ "eval_rougeL": 0.5200907337780047,
885
+ "eval_rougeLsum": 0.6372896614836894,
886
+ "eval_runtime": 15.0043,
887
+ "eval_samples_per_second": 0.666,
888
+ "eval_steps_per_second": 0.333,
889
+ "step": 8800
890
+ },
891
+ {
892
+ "epoch": 1.03,
893
+ "grad_norm": 0.24036027491092682,
894
+ "learning_rate": 0.00014875665821631015,
895
+ "loss": 1.5364,
896
+ "step": 9000
897
+ },
898
+ {
899
+ "epoch": 1.03,
900
+ "eval_bertscore": 0.7327737808227539,
901
+ "eval_loss": 1.7339435815811157,
902
+ "eval_rouge1": 0.6568524178922349,
903
+ "eval_rouge2": 0.35560270713543163,
904
+ "eval_rougeL": 0.5310443670833082,
905
+ "eval_rougeLsum": 0.6480993679097387,
906
+ "eval_runtime": 14.9303,
907
+ "eval_samples_per_second": 0.67,
908
+ "eval_steps_per_second": 0.335,
909
+ "step": 9000
910
+ },
911
+ {
912
+ "epoch": 1.05,
913
+ "grad_norm": 0.2729027271270752,
914
+ "learning_rate": 0.0001476172843022759,
915
+ "loss": 1.5182,
916
+ "step": 9200
917
+ },
918
+ {
919
+ "epoch": 1.05,
920
+ "eval_bertscore": 0.7334672212600708,
921
+ "eval_loss": 1.739061713218689,
922
+ "eval_rouge1": 0.6552962187824329,
923
+ "eval_rouge2": 0.35210314124279196,
924
+ "eval_rougeL": 0.5272039052368354,
925
+ "eval_rougeLsum": 0.6437473533492806,
926
+ "eval_runtime": 15.5418,
927
+ "eval_samples_per_second": 0.643,
928
+ "eval_steps_per_second": 0.322,
929
+ "step": 9200
930
+ },
931
+ {
932
+ "epoch": 1.07,
933
+ "grad_norm": 0.2909716069698334,
934
+ "learning_rate": 0.00014647791038824168,
935
+ "loss": 1.5276,
936
+ "step": 9400
937
+ },
938
+ {
939
+ "epoch": 1.07,
940
+ "eval_bertscore": 0.7288902997970581,
941
+ "eval_loss": 1.736944556236267,
942
+ "eval_rouge1": 0.6533271685598301,
943
+ "eval_rouge2": 0.35279315321532184,
944
+ "eval_rougeL": 0.5262688234671329,
945
+ "eval_rougeLsum": 0.6424084937151033,
946
+ "eval_runtime": 15.1115,
947
+ "eval_samples_per_second": 0.662,
948
+ "eval_steps_per_second": 0.331,
949
+ "step": 9400
950
+ },
951
+ {
952
+ "epoch": 1.09,
953
+ "grad_norm": 0.3035859763622284,
954
+ "learning_rate": 0.00014533853647420743,
955
+ "loss": 1.5445,
956
+ "step": 9600
957
+ },
958
+ {
959
+ "epoch": 1.09,
960
+ "eval_bertscore": 0.7308284044265747,
961
+ "eval_loss": 1.737762689590454,
962
+ "eval_rouge1": 0.6619725777891359,
963
+ "eval_rouge2": 0.3611963714506864,
964
+ "eval_rougeL": 0.5363802967084452,
965
+ "eval_rougeLsum": 0.6516690557971352,
966
+ "eval_runtime": 14.9932,
967
+ "eval_samples_per_second": 0.667,
968
+ "eval_steps_per_second": 0.333,
969
+ "step": 9600
970
+ },
971
+ {
972
+ "epoch": 1.12,
973
+ "grad_norm": 0.26574915647506714,
974
+ "learning_rate": 0.0001441991625601732,
975
+ "loss": 1.5342,
976
+ "step": 9800
977
+ },
978
+ {
979
+ "epoch": 1.12,
980
+ "eval_bertscore": 0.7328712344169617,
981
+ "eval_loss": 1.7393991947174072,
982
+ "eval_rouge1": 0.6856504003396884,
983
+ "eval_rouge2": 0.3761098841062477,
984
+ "eval_rougeL": 0.555477293163325,
985
+ "eval_rougeLsum": 0.6757574283262289,
986
+ "eval_runtime": 14.8121,
987
+ "eval_samples_per_second": 0.675,
988
+ "eval_steps_per_second": 0.338,
989
+ "step": 9800
990
+ },
991
+ {
992
+ "epoch": 1.14,
993
+ "grad_norm": 0.315468430519104,
994
+ "learning_rate": 0.00014305978864613897,
995
+ "loss": 1.543,
996
+ "step": 10000
997
+ },
998
+ {
999
+ "epoch": 1.14,
1000
+ "eval_bertscore": 0.7349387407302856,
1001
+ "eval_loss": 1.7352710962295532,
1002
+ "eval_rouge1": 0.6749953128982036,
1003
+ "eval_rouge2": 0.3720385250530084,
1004
+ "eval_rougeL": 0.5472261566474382,
1005
+ "eval_rougeLsum": 0.6657643539219252,
1006
+ "eval_runtime": 14.909,
1007
+ "eval_samples_per_second": 0.671,
1008
+ "eval_steps_per_second": 0.335,
1009
+ "step": 10000
1010
+ },
1011
+ {
1012
+ "epoch": 1.16,
1013
+ "grad_norm": 0.29815027117729187,
1014
+ "learning_rate": 0.00014192041473210472,
1015
+ "loss": 1.5547,
1016
+ "step": 10200
1017
+ },
1018
+ {
1019
+ "epoch": 1.16,
1020
+ "eval_bertscore": 0.7359883189201355,
1021
+ "eval_loss": 1.7269136905670166,
1022
+ "eval_rouge1": 0.6561141614088863,
1023
+ "eval_rouge2": 0.3606175666303814,
1024
+ "eval_rougeL": 0.5302270771032793,
1025
+ "eval_rougeLsum": 0.6446912079521883,
1026
+ "eval_runtime": 14.9527,
1027
+ "eval_samples_per_second": 0.669,
1028
+ "eval_steps_per_second": 0.334,
1029
+ "step": 10200
1030
+ },
1031
+ {
1032
+ "epoch": 1.18,
1033
+ "grad_norm": 0.3595702350139618,
1034
+ "learning_rate": 0.00014078104081807047,
1035
+ "loss": 1.5567,
1036
+ "step": 10400
1037
+ },
1038
+ {
1039
+ "epoch": 1.18,
1040
+ "eval_bertscore": 0.7328116297721863,
1041
+ "eval_loss": 1.7341644763946533,
1042
+ "eval_rouge1": 0.6420332714823549,
1043
+ "eval_rouge2": 0.35094864549032,
1044
+ "eval_rougeL": 0.5179556761398367,
1045
+ "eval_rougeLsum": 0.631987397226809,
1046
+ "eval_runtime": 15.1438,
1047
+ "eval_samples_per_second": 0.66,
1048
+ "eval_steps_per_second": 0.33,
1049
+ "step": 10400
1050
+ },
1051
+ {
1052
+ "epoch": 1.21,
1053
+ "grad_norm": 0.2718666195869446,
1054
+ "learning_rate": 0.00013964166690403623,
1055
+ "loss": 1.5408,
1056
+ "step": 10600
1057
+ },
1058
+ {
1059
+ "epoch": 1.21,
1060
+ "eval_bertscore": 0.7337731122970581,
1061
+ "eval_loss": 1.7330901622772217,
1062
+ "eval_rouge1": 0.661681342484687,
1063
+ "eval_rouge2": 0.3626833509973693,
1064
+ "eval_rougeL": 0.5329424447373774,
1065
+ "eval_rougeLsum": 0.6519750177144633,
1066
+ "eval_runtime": 14.8142,
1067
+ "eval_samples_per_second": 0.675,
1068
+ "eval_steps_per_second": 0.338,
1069
+ "step": 10600
1070
+ },
1071
+ {
1072
+ "epoch": 1.23,
1073
+ "grad_norm": 0.29183274507522583,
1074
+ "learning_rate": 0.00013850229299000198,
1075
+ "loss": 1.5422,
1076
+ "step": 10800
1077
+ },
1078
+ {
1079
+ "epoch": 1.23,
1080
+ "eval_bertscore": 0.7331051230430603,
1081
+ "eval_loss": 1.7297636270523071,
1082
+ "eval_rouge1": 0.6655497978238063,
1083
+ "eval_rouge2": 0.3614235788441926,
1084
+ "eval_rougeL": 0.5327210061667442,
1085
+ "eval_rougeLsum": 0.6548836840483913,
1086
+ "eval_runtime": 15.1359,
1087
+ "eval_samples_per_second": 0.661,
1088
+ "eval_steps_per_second": 0.33,
1089
+ "step": 10800
1090
+ },
1091
+ {
1092
+ "epoch": 1.25,
1093
+ "grad_norm": 0.30979740619659424,
1094
+ "learning_rate": 0.00013736291907596776,
1095
+ "loss": 1.5372,
1096
+ "step": 11000
1097
+ },
1098
+ {
1099
+ "epoch": 1.25,
1100
+ "eval_bertscore": 0.7312799692153931,
1101
+ "eval_loss": 1.732444167137146,
1102
+ "eval_rouge1": 0.6568292865033993,
1103
+ "eval_rouge2": 0.35876682221562006,
1104
+ "eval_rougeL": 0.5300878844981931,
1105
+ "eval_rougeLsum": 0.6461751645858989,
1106
+ "eval_runtime": 14.819,
1107
+ "eval_samples_per_second": 0.675,
1108
+ "eval_steps_per_second": 0.337,
1109
+ "step": 11000
1110
+ },
1111
+ {
1112
+ "epoch": 1.28,
1113
+ "grad_norm": 0.31343138217926025,
1114
+ "learning_rate": 0.0001362235451619335,
1115
+ "loss": 1.5301,
1116
+ "step": 11200
1117
+ },
1118
+ {
1119
+ "epoch": 1.28,
1120
+ "eval_bertscore": 0.7317885160446167,
1121
+ "eval_loss": 1.7358499765396118,
1122
+ "eval_rouge1": 0.6548673097943329,
1123
+ "eval_rouge2": 0.3609116081432997,
1124
+ "eval_rougeL": 0.5279887650752133,
1125
+ "eval_rougeLsum": 0.6466232329097188,
1126
+ "eval_runtime": 14.8259,
1127
+ "eval_samples_per_second": 0.674,
1128
+ "eval_steps_per_second": 0.337,
1129
+ "step": 11200
1130
+ },
1131
+ {
1132
+ "epoch": 1.3,
1133
+ "grad_norm": 0.36181533336639404,
1134
+ "learning_rate": 0.0001350841712478993,
1135
+ "loss": 1.5421,
1136
+ "step": 11400
1137
+ },
1138
+ {
1139
+ "epoch": 1.3,
1140
+ "eval_bertscore": 0.7316756248474121,
1141
+ "eval_loss": 1.7282969951629639,
1142
+ "eval_rouge1": 0.6551882964480251,
1143
+ "eval_rouge2": 0.3580708921400697,
1144
+ "eval_rougeL": 0.5255367305995147,
1145
+ "eval_rougeLsum": 0.6449192953008009,
1146
+ "eval_runtime": 14.8816,
1147
+ "eval_samples_per_second": 0.672,
1148
+ "eval_steps_per_second": 0.336,
1149
+ "step": 11400
1150
+ },
1151
+ {
1152
+ "epoch": 1.32,
1153
+ "grad_norm": 0.30600836873054504,
1154
+ "learning_rate": 0.00013394479733386505,
1155
+ "loss": 1.5538,
1156
+ "step": 11600
1157
+ },
1158
+ {
1159
+ "epoch": 1.32,
1160
+ "eval_bertscore": 0.7311854362487793,
1161
+ "eval_loss": 1.7313562631607056,
1162
+ "eval_rouge1": 0.6592751199424156,
1163
+ "eval_rouge2": 0.35802855072854206,
1164
+ "eval_rougeL": 0.5297288176377084,
1165
+ "eval_rougeLsum": 0.6489455314962717,
1166
+ "eval_runtime": 15.0693,
1167
+ "eval_samples_per_second": 0.664,
1168
+ "eval_steps_per_second": 0.332,
1169
+ "step": 11600
1170
+ },
1171
+ {
1172
+ "epoch": 1.34,
1173
+ "grad_norm": 0.29904893040657043,
1174
+ "learning_rate": 0.0001328054234198308,
1175
+ "loss": 1.5328,
1176
+ "step": 11800
1177
+ },
1178
+ {
1179
+ "epoch": 1.34,
1180
+ "eval_bertscore": 0.7312635183334351,
1181
+ "eval_loss": 1.7318429946899414,
1182
+ "eval_rouge1": 0.6577169369077195,
1183
+ "eval_rouge2": 0.3582474830918887,
1184
+ "eval_rougeL": 0.5314990647771975,
1185
+ "eval_rougeLsum": 0.6454785220479866,
1186
+ "eval_runtime": 15.0235,
1187
+ "eval_samples_per_second": 0.666,
1188
+ "eval_steps_per_second": 0.333,
1189
+ "step": 11800
1190
+ },
1191
+ {
1192
+ "epoch": 1.37,
1193
+ "grad_norm": 0.3025416433811188,
1194
+ "learning_rate": 0.00013166604950579658,
1195
+ "loss": 1.5349,
1196
+ "step": 12000
1197
+ },
1198
+ {
1199
+ "epoch": 1.37,
1200
+ "eval_bertscore": 0.7325812578201294,
1201
+ "eval_loss": 1.7309118509292603,
1202
+ "eval_rouge1": 0.6629133074951261,
1203
+ "eval_rouge2": 0.3678158453940578,
1204
+ "eval_rougeL": 0.5380936907276155,
1205
+ "eval_rougeLsum": 0.654883061928214,
1206
+ "eval_runtime": 14.7666,
1207
+ "eval_samples_per_second": 0.677,
1208
+ "eval_steps_per_second": 0.339,
1209
+ "step": 12000
1210
+ },
1211
+ {
1212
+ "epoch": 1.39,
1213
+ "grad_norm": 0.34982389211654663,
1214
+ "learning_rate": 0.00013052667559176233,
1215
+ "loss": 1.5513,
1216
+ "step": 12200
1217
+ },
1218
+ {
1219
+ "epoch": 1.39,
1220
+ "eval_bertscore": 0.7340582609176636,
1221
+ "eval_loss": 1.7363474369049072,
1222
+ "eval_rouge1": 0.6555817937418287,
1223
+ "eval_rouge2": 0.35630500078358396,
1224
+ "eval_rougeL": 0.5272412353478366,
1225
+ "eval_rougeLsum": 0.6445837479327643,
1226
+ "eval_runtime": 14.9664,
1227
+ "eval_samples_per_second": 0.668,
1228
+ "eval_steps_per_second": 0.334,
1229
+ "step": 12200
1230
+ },
1231
+ {
1232
+ "epoch": 1.41,
1233
+ "grad_norm": 0.35809043049812317,
1234
+ "learning_rate": 0.0001293873016777281,
1235
+ "loss": 1.5444,
1236
+ "step": 12400
1237
+ },
1238
+ {
1239
+ "epoch": 1.41,
1240
+ "eval_bertscore": 0.7334069013595581,
1241
+ "eval_loss": 1.7328729629516602,
1242
+ "eval_rouge1": 0.6617971237669364,
1243
+ "eval_rouge2": 0.35951260376512423,
1244
+ "eval_rougeL": 0.5345512305507059,
1245
+ "eval_rougeLsum": 0.648363531132752,
1246
+ "eval_runtime": 15.2146,
1247
+ "eval_samples_per_second": 0.657,
1248
+ "eval_steps_per_second": 0.329,
1249
+ "step": 12400
1250
+ },
1251
+ {
1252
+ "epoch": 1.44,
1253
+ "grad_norm": 0.2954196631908417,
1254
+ "learning_rate": 0.00012824792776369387,
1255
+ "loss": 1.5406,
1256
+ "step": 12600
1257
+ },
1258
+ {
1259
+ "epoch": 1.44,
1260
+ "eval_bertscore": 0.7321678400039673,
1261
+ "eval_loss": 1.7335160970687866,
1262
+ "eval_rouge1": 0.6573625593086756,
1263
+ "eval_rouge2": 0.36210525247389347,
1264
+ "eval_rougeL": 0.5379361120230158,
1265
+ "eval_rougeLsum": 0.6459787883452857,
1266
+ "eval_runtime": 14.8942,
1267
+ "eval_samples_per_second": 0.671,
1268
+ "eval_steps_per_second": 0.336,
1269
+ "step": 12600
1270
+ },
1271
+ {
1272
+ "epoch": 1.46,
1273
+ "grad_norm": 0.32190588116645813,
1274
+ "learning_rate": 0.00012710855384965962,
1275
+ "loss": 1.5491,
1276
+ "step": 12800
1277
+ },
1278
+ {
1279
+ "epoch": 1.46,
1280
+ "eval_bertscore": 0.7346011400222778,
1281
+ "eval_loss": 1.7364966869354248,
1282
+ "eval_rouge1": 0.6481210247390559,
1283
+ "eval_rouge2": 0.3521173896017687,
1284
+ "eval_rougeL": 0.5240500581372636,
1285
+ "eval_rougeLsum": 0.63706442433335,
1286
+ "eval_runtime": 14.923,
1287
+ "eval_samples_per_second": 0.67,
1288
+ "eval_steps_per_second": 0.335,
1289
+ "step": 12800
1290
+ },
1291
+ {
1292
+ "epoch": 1.48,
1293
+ "grad_norm": 0.33323267102241516,
1294
+ "learning_rate": 0.00012596917993562537,
1295
+ "loss": 1.5596,
1296
+ "step": 13000
1297
+ },
1298
+ {
1299
+ "epoch": 1.48,
1300
+ "eval_bertscore": 0.7331587076187134,
1301
+ "eval_loss": 1.7332260608673096,
1302
+ "eval_rouge1": 0.6561257401878793,
1303
+ "eval_rouge2": 0.3548063723792664,
1304
+ "eval_rougeL": 0.527807776001489,
1305
+ "eval_rougeLsum": 0.6451911907984706,
1306
+ "eval_runtime": 15.4703,
1307
+ "eval_samples_per_second": 0.646,
1308
+ "eval_steps_per_second": 0.323,
1309
+ "step": 13000
1310
+ },
1311
+ {
1312
+ "epoch": 1.5,
1313
+ "grad_norm": 0.3564057946205139,
1314
+ "learning_rate": 0.00012482980602159113,
1315
+ "loss": 1.5261,
1316
+ "step": 13200
1317
+ },
1318
+ {
1319
+ "epoch": 1.5,
1320
+ "eval_bertscore": 0.7306063771247864,
1321
+ "eval_loss": 1.7368810176849365,
1322
+ "eval_rouge1": 0.637722723890071,
1323
+ "eval_rouge2": 0.3455358728458236,
1324
+ "eval_rougeL": 0.5136372690435154,
1325
+ "eval_rougeLsum": 0.6273570573595115,
1326
+ "eval_runtime": 15.3533,
1327
+ "eval_samples_per_second": 0.651,
1328
+ "eval_steps_per_second": 0.326,
1329
+ "step": 13200
1330
+ },
1331
+ {
1332
+ "epoch": 1.53,
1333
+ "grad_norm": 0.29219934344291687,
1334
+ "learning_rate": 0.0001236904321075569,
1335
+ "loss": 1.519,
1336
+ "step": 13400
1337
+ },
1338
+ {
1339
+ "epoch": 1.53,
1340
+ "eval_bertscore": 0.7338696122169495,
1341
+ "eval_loss": 1.734724998474121,
1342
+ "eval_rouge1": 0.6442107446420164,
1343
+ "eval_rouge2": 0.3494748457109431,
1344
+ "eval_rougeL": 0.5207483892007314,
1345
+ "eval_rougeLsum": 0.632886404907802,
1346
+ "eval_runtime": 15.3077,
1347
+ "eval_samples_per_second": 0.653,
1348
+ "eval_steps_per_second": 0.327,
1349
+ "step": 13400
1350
+ },
1351
+ {
1352
+ "epoch": 1.55,
1353
+ "grad_norm": 0.34681758284568787,
1354
+ "learning_rate": 0.00012255105819352266,
1355
+ "loss": 1.5419,
1356
+ "step": 13600
1357
+ },
1358
+ {
1359
+ "epoch": 1.55,
1360
+ "eval_bertscore": 0.7350045442581177,
1361
+ "eval_loss": 1.7329858541488647,
1362
+ "eval_rouge1": 0.6606839869796519,
1363
+ "eval_rouge2": 0.362188561160822,
1364
+ "eval_rougeL": 0.5342033818317451,
1365
+ "eval_rougeLsum": 0.6493340000068861,
1366
+ "eval_runtime": 15.44,
1367
+ "eval_samples_per_second": 0.648,
1368
+ "eval_steps_per_second": 0.324,
1369
+ "step": 13600
1370
+ },
1371
+ {
1372
+ "epoch": 1.57,
1373
+ "grad_norm": 0.3043666481971741,
1374
+ "learning_rate": 0.00012141168427948844,
1375
+ "loss": 1.5402,
1376
+ "step": 13800
1377
+ },
1378
+ {
1379
+ "epoch": 1.57,
1380
+ "eval_bertscore": 0.7363221645355225,
1381
+ "eval_loss": 1.7308530807495117,
1382
+ "eval_rouge1": 0.6638252384356028,
1383
+ "eval_rouge2": 0.3643237697892826,
1384
+ "eval_rougeL": 0.5403775887381331,
1385
+ "eval_rougeLsum": 0.6537260000827279,
1386
+ "eval_runtime": 14.7668,
1387
+ "eval_samples_per_second": 0.677,
1388
+ "eval_steps_per_second": 0.339,
1389
+ "step": 13800
1390
+ },
1391
+ {
1392
+ "epoch": 1.59,
1393
+ "grad_norm": 0.4073585867881775,
1394
+ "learning_rate": 0.00012027231036545419,
1395
+ "loss": 1.5256,
1396
+ "step": 14000
1397
+ },
1398
+ {
1399
+ "epoch": 1.59,
1400
+ "eval_bertscore": 0.7310279607772827,
1401
+ "eval_loss": 1.7326784133911133,
1402
+ "eval_rouge1": 0.6609594314120198,
1403
+ "eval_rouge2": 0.3601530714440473,
1404
+ "eval_rougeL": 0.5344452687135626,
1405
+ "eval_rougeLsum": 0.6480936554342305,
1406
+ "eval_runtime": 14.8565,
1407
+ "eval_samples_per_second": 0.673,
1408
+ "eval_steps_per_second": 0.337,
1409
+ "step": 14000
1410
+ },
1411
+ {
1412
+ "epoch": 1.62,
1413
+ "grad_norm": 0.3211813271045685,
1414
+ "learning_rate": 0.00011913293645141995,
1415
+ "loss": 1.5366,
1416
+ "step": 14200
1417
+ },
1418
+ {
1419
+ "epoch": 1.62,
1420
+ "eval_bertscore": 0.7356667518615723,
1421
+ "eval_loss": 1.7280094623565674,
1422
+ "eval_rouge1": 0.6519353227375031,
1423
+ "eval_rouge2": 0.3587025716186173,
1424
+ "eval_rougeL": 0.5306356200586075,
1425
+ "eval_rougeLsum": 0.6408870347994059,
1426
+ "eval_runtime": 14.9264,
1427
+ "eval_samples_per_second": 0.67,
1428
+ "eval_steps_per_second": 0.335,
1429
+ "step": 14200
1430
+ },
1431
+ {
1432
+ "epoch": 1.64,
1433
+ "grad_norm": 0.32776832580566406,
1434
+ "learning_rate": 0.00011799356253738571,
1435
+ "loss": 1.5504,
1436
+ "step": 14400
1437
+ },
1438
+ {
1439
+ "epoch": 1.64,
1440
+ "eval_bertscore": 0.7331353425979614,
1441
+ "eval_loss": 1.7308950424194336,
1442
+ "eval_rouge1": 0.6627702292814652,
1443
+ "eval_rouge2": 0.36117793957379707,
1444
+ "eval_rougeL": 0.5369305446079228,
1445
+ "eval_rougeLsum": 0.6516924083980089,
1446
+ "eval_runtime": 16.0138,
1447
+ "eval_samples_per_second": 0.624,
1448
+ "eval_steps_per_second": 0.312,
1449
+ "step": 14400
1450
+ },
1451
+ {
1452
+ "epoch": 1.66,
1453
+ "grad_norm": 0.3209726810455322,
1454
+ "learning_rate": 0.00011685418862335147,
1455
+ "loss": 1.5473,
1456
+ "step": 14600
1457
+ },
1458
+ {
1459
+ "epoch": 1.66,
1460
+ "eval_bertscore": 0.732498824596405,
1461
+ "eval_loss": 1.7328402996063232,
1462
+ "eval_rouge1": 0.6482679740803596,
1463
+ "eval_rouge2": 0.3538726087405498,
1464
+ "eval_rougeL": 0.5267677183598017,
1465
+ "eval_rougeLsum": 0.6366529460029322,
1466
+ "eval_runtime": 15.0195,
1467
+ "eval_samples_per_second": 0.666,
1468
+ "eval_steps_per_second": 0.333,
1469
+ "step": 14600
1470
+ },
1471
+ {
1472
+ "epoch": 1.69,
1473
+ "grad_norm": 0.3174591064453125,
1474
+ "learning_rate": 0.00011571481470931725,
1475
+ "loss": 1.5568,
1476
+ "step": 14800
1477
+ },
1478
+ {
1479
+ "epoch": 1.69,
1480
+ "eval_bertscore": 0.7335298657417297,
1481
+ "eval_loss": 1.7310253381729126,
1482
+ "eval_rouge1": 0.6560468577439627,
1483
+ "eval_rouge2": 0.36039371229175,
1484
+ "eval_rougeL": 0.5318708569729291,
1485
+ "eval_rougeLsum": 0.6444857558837042,
1486
+ "eval_runtime": 14.9774,
1487
+ "eval_samples_per_second": 0.668,
1488
+ "eval_steps_per_second": 0.334,
1489
+ "step": 14800
1490
+ },
1491
+ {
1492
+ "epoch": 1.71,
1493
+ "grad_norm": 0.2936408817768097,
1494
+ "learning_rate": 0.000114575440795283,
1495
+ "loss": 1.5345,
1496
+ "step": 15000
1497
+ },
1498
+ {
1499
+ "epoch": 1.71,
1500
+ "eval_bertscore": 0.7322725057601929,
1501
+ "eval_loss": 1.7270629405975342,
1502
+ "eval_rouge1": 0.6387060930656672,
1503
+ "eval_rouge2": 0.3480508127989137,
1504
+ "eval_rougeL": 0.5148670834213287,
1505
+ "eval_rougeLsum": 0.6273654952601909,
1506
+ "eval_runtime": 15.6687,
1507
+ "eval_samples_per_second": 0.638,
1508
+ "eval_steps_per_second": 0.319,
1509
+ "step": 15000
1510
+ },
1511
+ {
1512
+ "epoch": 1.73,
1513
+ "grad_norm": 0.32960689067840576,
1514
+ "learning_rate": 0.00011343606688124875,
1515
+ "loss": 1.5362,
1516
+ "step": 15200
1517
+ },
1518
+ {
1519
+ "epoch": 1.73,
1520
+ "eval_bertscore": 0.7337037920951843,
1521
+ "eval_loss": 1.7287395000457764,
1522
+ "eval_rouge1": 0.6476816970229771,
1523
+ "eval_rouge2": 0.3532248216683249,
1524
+ "eval_rougeL": 0.5253136618838716,
1525
+ "eval_rougeLsum": 0.6347493764394183,
1526
+ "eval_runtime": 15.0045,
1527
+ "eval_samples_per_second": 0.666,
1528
+ "eval_steps_per_second": 0.333,
1529
+ "step": 15200
1530
+ },
1531
+ {
1532
+ "epoch": 1.75,
1533
+ "grad_norm": 0.33265602588653564,
1534
+ "learning_rate": 0.00011229669296721452,
1535
+ "loss": 1.5215,
1536
+ "step": 15400
1537
+ },
1538
+ {
1539
+ "epoch": 1.75,
1540
+ "eval_bertscore": 0.7330806851387024,
1541
+ "eval_loss": 1.7265052795410156,
1542
+ "eval_rouge1": 0.6529393512177359,
1543
+ "eval_rouge2": 0.36182153145062224,
1544
+ "eval_rougeL": 0.5317061134915853,
1545
+ "eval_rougeLsum": 0.6413066299251913,
1546
+ "eval_runtime": 15.0256,
1547
+ "eval_samples_per_second": 0.666,
1548
+ "eval_steps_per_second": 0.333,
1549
+ "step": 15400
1550
+ },
1551
+ {
1552
+ "epoch": 1.78,
1553
+ "grad_norm": 0.3436201512813568,
1554
+ "learning_rate": 0.00011115731905318027,
1555
+ "loss": 1.539,
1556
+ "step": 15600
1557
+ },
1558
+ {
1559
+ "epoch": 1.78,
1560
+ "eval_bertscore": 0.7335551977157593,
1561
+ "eval_loss": 1.7254730463027954,
1562
+ "eval_rouge1": 0.6388518781767971,
1563
+ "eval_rouge2": 0.3501853846588857,
1564
+ "eval_rougeL": 0.5196828245794569,
1565
+ "eval_rougeLsum": 0.629333993884722,
1566
+ "eval_runtime": 15.2595,
1567
+ "eval_samples_per_second": 0.655,
1568
+ "eval_steps_per_second": 0.328,
1569
+ "step": 15600
1570
+ },
1571
+ {
1572
+ "epoch": 1.8,
1573
+ "grad_norm": 0.3428190350532532,
1574
+ "learning_rate": 0.00011001794513914605,
1575
+ "loss": 1.5273,
1576
+ "step": 15800
1577
+ },
1578
+ {
1579
+ "epoch": 1.8,
1580
+ "eval_bertscore": 0.7331770658493042,
1581
+ "eval_loss": 1.7286018133163452,
1582
+ "eval_rouge1": 0.6581941047310954,
1583
+ "eval_rouge2": 0.36277983926897583,
1584
+ "eval_rougeL": 0.5336464680120501,
1585
+ "eval_rougeLsum": 0.6489239720278894,
1586
+ "eval_runtime": 14.8252,
1587
+ "eval_samples_per_second": 0.675,
1588
+ "eval_steps_per_second": 0.337,
1589
+ "step": 15800
1590
+ },
1591
+ {
1592
+ "epoch": 1.82,
1593
+ "grad_norm": 0.363164484500885,
1594
+ "learning_rate": 0.0001088785712251118,
1595
+ "loss": 1.5445,
1596
+ "step": 16000
1597
+ },
1598
+ {
1599
+ "epoch": 1.82,
1600
+ "eval_bertscore": 0.7377282977104187,
1601
+ "eval_loss": 1.7363064289093018,
1602
+ "eval_rouge1": 0.6547011011872876,
1603
+ "eval_rouge2": 0.3553220826957326,
1604
+ "eval_rougeL": 0.5256073814411315,
1605
+ "eval_rougeLsum": 0.6420095316923398,
1606
+ "eval_runtime": 14.8599,
1607
+ "eval_samples_per_second": 0.673,
1608
+ "eval_steps_per_second": 0.336,
1609
+ "step": 16000
1610
+ },
1611
+ {
1612
+ "epoch": 1.85,
1613
+ "grad_norm": 0.3098333775997162,
1614
+ "learning_rate": 0.00010773919731107757,
1615
+ "loss": 1.5319,
1616
+ "step": 16200
1617
+ },
1618
+ {
1619
+ "epoch": 1.85,
1620
+ "eval_bertscore": 0.7324053645133972,
1621
+ "eval_loss": 1.7284066677093506,
1622
+ "eval_rouge1": 0.6477379941950916,
1623
+ "eval_rouge2": 0.3535918140554809,
1624
+ "eval_rougeL": 0.5226838544730126,
1625
+ "eval_rougeLsum": 0.6373271915355557,
1626
+ "eval_runtime": 14.9318,
1627
+ "eval_samples_per_second": 0.67,
1628
+ "eval_steps_per_second": 0.335,
1629
+ "step": 16200
1630
+ },
1631
+ {
1632
+ "epoch": 1.87,
1633
+ "grad_norm": 0.3637208938598633,
1634
+ "learning_rate": 0.00010659982339704332,
1635
+ "loss": 1.5442,
1636
+ "step": 16400
1637
+ },
1638
+ {
1639
+ "epoch": 1.87,
1640
+ "eval_bertscore": 0.7347462773323059,
1641
+ "eval_loss": 1.7252963781356812,
1642
+ "eval_rouge1": 0.6494449840449819,
1643
+ "eval_rouge2": 0.3586550050575282,
1644
+ "eval_rougeL": 0.5275675395159809,
1645
+ "eval_rougeLsum": 0.6396738714026391,
1646
+ "eval_runtime": 15.2218,
1647
+ "eval_samples_per_second": 0.657,
1648
+ "eval_steps_per_second": 0.328,
1649
+ "step": 16400
1650
+ },
1651
+ {
1652
+ "epoch": 1.89,
1653
+ "grad_norm": 0.35197457671165466,
1654
+ "learning_rate": 0.00010546044948300908,
1655
+ "loss": 1.5131,
1656
+ "step": 16600
1657
+ },
1658
+ {
1659
+ "epoch": 1.89,
1660
+ "eval_bertscore": 0.7329785227775574,
1661
+ "eval_loss": 1.7285687923431396,
1662
+ "eval_rouge1": 0.6582047811143328,
1663
+ "eval_rouge2": 0.3637700686094697,
1664
+ "eval_rougeL": 0.5355021948480279,
1665
+ "eval_rougeLsum": 0.6483245595148677,
1666
+ "eval_runtime": 14.8772,
1667
+ "eval_samples_per_second": 0.672,
1668
+ "eval_steps_per_second": 0.336,
1669
+ "step": 16600
1670
+ },
1671
+ {
1672
+ "epoch": 1.91,
1673
+ "grad_norm": 0.3406757116317749,
1674
+ "learning_rate": 0.00010432107556897486,
1675
+ "loss": 1.5394,
1676
+ "step": 16800
1677
+ },
1678
+ {
1679
+ "epoch": 1.91,
1680
+ "eval_bertscore": 0.7345961332321167,
1681
+ "eval_loss": 1.7324028015136719,
1682
+ "eval_rouge1": 0.6408293615351552,
1683
+ "eval_rouge2": 0.3520120690778129,
1684
+ "eval_rougeL": 0.5145218014745592,
1685
+ "eval_rougeLsum": 0.6297802607384266,
1686
+ "eval_runtime": 15.1044,
1687
+ "eval_samples_per_second": 0.662,
1688
+ "eval_steps_per_second": 0.331,
1689
+ "step": 16800
1690
+ },
1691
+ {
1692
+ "epoch": 1.94,
1693
+ "grad_norm": 0.3417683243751526,
1694
+ "learning_rate": 0.00010318170165494061,
1695
+ "loss": 1.526,
1696
+ "step": 17000
1697
+ },
1698
+ {
1699
+ "epoch": 1.94,
1700
+ "eval_bertscore": 0.735752522945404,
1701
+ "eval_loss": 1.7288110256195068,
1702
+ "eval_rouge1": 0.641158513352794,
1703
+ "eval_rouge2": 0.3544166440855814,
1704
+ "eval_rougeL": 0.5215201980495414,
1705
+ "eval_rougeLsum": 0.630550065494593,
1706
+ "eval_runtime": 15.0797,
1707
+ "eval_samples_per_second": 0.663,
1708
+ "eval_steps_per_second": 0.332,
1709
+ "step": 17000
1710
+ },
1711
+ {
1712
+ "epoch": 1.96,
1713
+ "grad_norm": 0.3256611227989197,
1714
+ "learning_rate": 0.00010204232774090639,
1715
+ "loss": 1.5484,
1716
+ "step": 17200
1717
+ },
1718
+ {
1719
+ "epoch": 1.96,
1720
+ "eval_bertscore": 0.7356327772140503,
1721
+ "eval_loss": 1.7305186986923218,
1722
+ "eval_rouge1": 0.6400269226515611,
1723
+ "eval_rouge2": 0.3502884634173268,
1724
+ "eval_rougeL": 0.517312321281175,
1725
+ "eval_rougeLsum": 0.6284556997614409,
1726
+ "eval_runtime": 15.4097,
1727
+ "eval_samples_per_second": 0.649,
1728
+ "eval_steps_per_second": 0.324,
1729
+ "step": 17200
1730
+ },
1731
+ {
1732
+ "epoch": 1.98,
1733
+ "grad_norm": 0.4035187363624573,
1734
+ "learning_rate": 0.00010090295382687213,
1735
+ "loss": 1.5261,
1736
+ "step": 17400
1737
+ },
1738
+ {
1739
+ "epoch": 1.98,
1740
+ "eval_bertscore": 0.7339992523193359,
1741
+ "eval_loss": 1.7282793521881104,
1742
+ "eval_rouge1": 0.6335770390416183,
1743
+ "eval_rouge2": 0.34592404578075897,
1744
+ "eval_rougeL": 0.5109045259792113,
1745
+ "eval_rougeLsum": 0.6218413683710426,
1746
+ "eval_runtime": 15.1959,
1747
+ "eval_samples_per_second": 0.658,
1748
+ "eval_steps_per_second": 0.329,
1749
+ "step": 17400
1750
+ },
1751
+ {
1752
+ "epoch": 2.0,
1753
+ "grad_norm": 0.34987062215805054,
1754
+ "learning_rate": 9.97635799128379e-05,
1755
+ "loss": 1.5199,
1756
+ "step": 17600
1757
+ },
1758
+ {
1759
+ "epoch": 2.0,
1760
+ "eval_bertscore": 0.7326329946517944,
1761
+ "eval_loss": 1.7544715404510498,
1762
+ "eval_rouge1": 0.6451558045750205,
1763
+ "eval_rouge2": 0.35565806935653943,
1764
+ "eval_rougeL": 0.5217034865840529,
1765
+ "eval_rougeLsum": 0.6329869715356753,
1766
+ "eval_runtime": 15.0351,
1767
+ "eval_samples_per_second": 0.665,
1768
+ "eval_steps_per_second": 0.333,
1769
+ "step": 17600
1770
+ },
1771
+ {
1772
+ "epoch": 2.03,
1773
+ "grad_norm": 0.37184038758277893,
1774
+ "learning_rate": 9.862420599880366e-05,
1775
+ "loss": 1.41,
1776
+ "step": 17800
1777
+ },
1778
+ {
1779
+ "epoch": 2.03,
1780
+ "eval_bertscore": 0.7315141558647156,
1781
+ "eval_loss": 1.7585878372192383,
1782
+ "eval_rouge1": 0.6469319193583706,
1783
+ "eval_rouge2": 0.3514447211469598,
1784
+ "eval_rougeL": 0.524755857688278,
1785
+ "eval_rougeLsum": 0.6350164781858667,
1786
+ "eval_runtime": 14.9583,
1787
+ "eval_samples_per_second": 0.669,
1788
+ "eval_steps_per_second": 0.334,
1789
+ "step": 17800
1790
+ },
1791
+ {
1792
+ "epoch": 2.05,
1793
+ "grad_norm": 0.3812776803970337,
1794
+ "learning_rate": 9.748483208476943e-05,
1795
+ "loss": 1.4132,
1796
+ "step": 18000
1797
+ },
1798
+ {
1799
+ "epoch": 2.05,
1800
+ "eval_bertscore": 0.7335561513900757,
1801
+ "eval_loss": 1.764611840248108,
1802
+ "eval_rouge1": 0.6381916780473581,
1803
+ "eval_rouge2": 0.3482510604092539,
1804
+ "eval_rougeL": 0.5162105225823392,
1805
+ "eval_rougeLsum": 0.627150245441782,
1806
+ "eval_runtime": 15.8515,
1807
+ "eval_samples_per_second": 0.631,
1808
+ "eval_steps_per_second": 0.315,
1809
+ "step": 18000
1810
+ },
1811
+ {
1812
+ "epoch": 2.07,
1813
+ "grad_norm": 0.45525220036506653,
1814
+ "learning_rate": 9.634545817073518e-05,
1815
+ "loss": 1.4,
1816
+ "step": 18200
1817
+ },
1818
+ {
1819
+ "epoch": 2.07,
1820
+ "eval_bertscore": 0.73627769947052,
1821
+ "eval_loss": 1.7585163116455078,
1822
+ "eval_rouge1": 0.6670097658027134,
1823
+ "eval_rouge2": 0.3658295359911405,
1824
+ "eval_rougeL": 0.5429667657900548,
1825
+ "eval_rougeLsum": 0.6543501745791419,
1826
+ "eval_runtime": 15.0301,
1827
+ "eval_samples_per_second": 0.665,
1828
+ "eval_steps_per_second": 0.333,
1829
+ "step": 18200
1830
+ },
1831
+ {
1832
+ "epoch": 2.1,
1833
+ "grad_norm": 0.37322184443473816,
1834
+ "learning_rate": 9.520608425670095e-05,
1835
+ "loss": 1.4293,
1836
+ "step": 18400
1837
+ },
1838
+ {
1839
+ "epoch": 2.1,
1840
+ "eval_bertscore": 0.730435848236084,
1841
+ "eval_loss": 1.764052391052246,
1842
+ "eval_rouge1": 0.6640215078213034,
1843
+ "eval_rouge2": 0.3625932287322054,
1844
+ "eval_rougeL": 0.5379978391335138,
1845
+ "eval_rougeLsum": 0.6542054656293199,
1846
+ "eval_runtime": 15.0762,
1847
+ "eval_samples_per_second": 0.663,
1848
+ "eval_steps_per_second": 0.332,
1849
+ "step": 18400
1850
+ },
1851
+ {
1852
+ "epoch": 2.12,
1853
+ "grad_norm": 0.4260891079902649,
1854
+ "learning_rate": 9.40667103426667e-05,
1855
+ "loss": 1.4077,
1856
+ "step": 18600
1857
+ },
1858
+ {
1859
+ "epoch": 2.12,
1860
+ "eval_bertscore": 0.7309869527816772,
1861
+ "eval_loss": 1.762108564376831,
1862
+ "eval_rouge1": 0.6571171081737958,
1863
+ "eval_rouge2": 0.35780421333141865,
1864
+ "eval_rougeL": 0.5320129270967632,
1865
+ "eval_rougeLsum": 0.64587787409523,
1866
+ "eval_runtime": 14.9004,
1867
+ "eval_samples_per_second": 0.671,
1868
+ "eval_steps_per_second": 0.336,
1869
+ "step": 18600
1870
+ },
1871
+ {
1872
+ "epoch": 2.14,
1873
+ "grad_norm": 0.39479926228523254,
1874
+ "learning_rate": 9.292733642863247e-05,
1875
+ "loss": 1.4165,
1876
+ "step": 18800
1877
+ },
1878
+ {
1879
+ "epoch": 2.14,
1880
+ "eval_bertscore": 0.7324444651603699,
1881
+ "eval_loss": 1.7607113122940063,
1882
+ "eval_rouge1": 0.6628398862884018,
1883
+ "eval_rouge2": 0.3627259806721216,
1884
+ "eval_rougeL": 0.5366106483832656,
1885
+ "eval_rougeLsum": 0.6528364858807157,
1886
+ "eval_runtime": 15.5766,
1887
+ "eval_samples_per_second": 0.642,
1888
+ "eval_steps_per_second": 0.321,
1889
+ "step": 18800
1890
+ },
1891
+ {
1892
+ "epoch": 2.16,
1893
+ "grad_norm": 0.39267703890800476,
1894
+ "learning_rate": 9.178796251459824e-05,
1895
+ "loss": 1.4123,
1896
+ "step": 19000
1897
+ },
1898
+ {
1899
+ "epoch": 2.16,
1900
+ "eval_bertscore": 0.7298994064331055,
1901
+ "eval_loss": 1.7668545246124268,
1902
+ "eval_rouge1": 0.6490850022857569,
1903
+ "eval_rouge2": 0.3532323419511264,
1904
+ "eval_rougeL": 0.5212823000193295,
1905
+ "eval_rougeLsum": 0.636442724466695,
1906
+ "eval_runtime": 14.9094,
1907
+ "eval_samples_per_second": 0.671,
1908
+ "eval_steps_per_second": 0.335,
1909
+ "step": 19000
1910
+ },
1911
+ {
1912
+ "epoch": 2.19,
1913
+ "grad_norm": 0.38221287727355957,
1914
+ "learning_rate": 9.0648588600564e-05,
1915
+ "loss": 1.401,
1916
+ "step": 19200
1917
+ },
1918
+ {
1919
+ "epoch": 2.19,
1920
+ "eval_bertscore": 0.7316875457763672,
1921
+ "eval_loss": 1.764147400856018,
1922
+ "eval_rouge1": 0.6490326710625849,
1923
+ "eval_rouge2": 0.3510351037900723,
1924
+ "eval_rougeL": 0.5239165028795836,
1925
+ "eval_rougeLsum": 0.6373687316421427,
1926
+ "eval_runtime": 15.1192,
1927
+ "eval_samples_per_second": 0.661,
1928
+ "eval_steps_per_second": 0.331,
1929
+ "step": 19200
1930
+ },
1931
+ {
1932
+ "epoch": 2.21,
1933
+ "grad_norm": 0.3653150200843811,
1934
+ "learning_rate": 8.950921468652976e-05,
1935
+ "loss": 1.4109,
1936
+ "step": 19400
1937
+ },
1938
+ {
1939
+ "epoch": 2.21,
1940
+ "eval_bertscore": 0.7348155975341797,
1941
+ "eval_loss": 1.7640550136566162,
1942
+ "eval_rouge1": 0.6462152873276823,
1943
+ "eval_rouge2": 0.3483599145461069,
1944
+ "eval_rougeL": 0.5193372430687719,
1945
+ "eval_rougeLsum": 0.6334254357511564,
1946
+ "eval_runtime": 14.9291,
1947
+ "eval_samples_per_second": 0.67,
1948
+ "eval_steps_per_second": 0.335,
1949
+ "step": 19400
1950
+ },
1951
+ {
1952
+ "epoch": 2.23,
1953
+ "grad_norm": 0.38049009442329407,
1954
+ "learning_rate": 8.836984077249551e-05,
1955
+ "loss": 1.4189,
1956
+ "step": 19600
1957
+ },
1958
+ {
1959
+ "epoch": 2.23,
1960
+ "eval_bertscore": 0.7357938885688782,
1961
+ "eval_loss": 1.7696326971054077,
1962
+ "eval_rouge1": 0.6377276221057538,
1963
+ "eval_rouge2": 0.3455397190390045,
1964
+ "eval_rougeL": 0.5118069428064842,
1965
+ "eval_rougeLsum": 0.6264501633078481,
1966
+ "eval_runtime": 14.8653,
1967
+ "eval_samples_per_second": 0.673,
1968
+ "eval_steps_per_second": 0.336,
1969
+ "step": 19600
1970
+ },
1971
+ {
1972
+ "epoch": 2.26,
1973
+ "grad_norm": 0.42111098766326904,
1974
+ "learning_rate": 8.723046685846128e-05,
1975
+ "loss": 1.4152,
1976
+ "step": 19800
1977
+ },
1978
+ {
1979
+ "epoch": 2.26,
1980
+ "eval_bertscore": 0.7339056134223938,
1981
+ "eval_loss": 1.7658218145370483,
1982
+ "eval_rouge1": 0.6494820372695989,
1983
+ "eval_rouge2": 0.34691658128805236,
1984
+ "eval_rougeL": 0.5193228965163086,
1985
+ "eval_rougeLsum": 0.6365347065687565,
1986
+ "eval_runtime": 15.3562,
1987
+ "eval_samples_per_second": 0.651,
1988
+ "eval_steps_per_second": 0.326,
1989
+ "step": 19800
1990
+ },
1991
+ {
1992
+ "epoch": 2.28,
1993
+ "grad_norm": 0.4452258050441742,
1994
+ "learning_rate": 8.609109294442704e-05,
1995
+ "loss": 1.4101,
1996
+ "step": 20000
1997
+ },
1998
+ {
1999
+ "epoch": 2.28,
2000
+ "eval_bertscore": 0.7296434640884399,
2001
+ "eval_loss": 1.7714240550994873,
2002
+ "eval_rouge1": 0.6565600824405751,
2003
+ "eval_rouge2": 0.3533618655201594,
2004
+ "eval_rougeL": 0.5263318202066467,
2005
+ "eval_rougeLsum": 0.6444964824298407,
2006
+ "eval_runtime": 14.8578,
2007
+ "eval_samples_per_second": 0.673,
2008
+ "eval_steps_per_second": 0.337,
2009
+ "step": 20000
2010
+ },
2011
+ {
2012
+ "epoch": 2.3,
2013
+ "grad_norm": 0.4030967652797699,
2014
+ "learning_rate": 8.495171903039281e-05,
2015
+ "loss": 1.4049,
2016
+ "step": 20200
2017
+ },
2018
+ {
2019
+ "epoch": 2.3,
2020
+ "eval_bertscore": 0.7307097315788269,
2021
+ "eval_loss": 1.774444580078125,
2022
+ "eval_rouge1": 0.6517204836155526,
2023
+ "eval_rouge2": 0.3521339653276223,
2024
+ "eval_rougeL": 0.5223211728244184,
2025
+ "eval_rougeLsum": 0.6398710531932736,
2026
+ "eval_runtime": 15.8543,
2027
+ "eval_samples_per_second": 0.631,
2028
+ "eval_steps_per_second": 0.315,
2029
+ "step": 20200
2030
+ },
2031
+ {
2032
+ "epoch": 2.32,
2033
+ "grad_norm": 0.33409813046455383,
2034
+ "learning_rate": 8.381234511635858e-05,
2035
+ "loss": 1.4243,
2036
+ "step": 20400
2037
+ },
2038
+ {
2039
+ "epoch": 2.32,
2040
+ "eval_bertscore": 0.7312101721763611,
2041
+ "eval_loss": 1.7654094696044922,
2042
+ "eval_rouge1": 0.6607249126293291,
2043
+ "eval_rouge2": 0.3545993249716188,
2044
+ "eval_rougeL": 0.5320161007986739,
2045
+ "eval_rougeLsum": 0.6503315335963733,
2046
+ "eval_runtime": 14.8739,
2047
+ "eval_samples_per_second": 0.672,
2048
+ "eval_steps_per_second": 0.336,
2049
+ "step": 20400
2050
+ },
2051
+ {
2052
+ "epoch": 2.35,
2053
+ "grad_norm": 0.4044789671897888,
2054
+ "learning_rate": 8.267297120232433e-05,
2055
+ "loss": 1.413,
2056
+ "step": 20600
2057
+ },
2058
+ {
2059
+ "epoch": 2.35,
2060
+ "eval_bertscore": 0.7342169880867004,
2061
+ "eval_loss": 1.769879937171936,
2062
+ "eval_rouge1": 0.6442777880355144,
2063
+ "eval_rouge2": 0.35006080708477183,
2064
+ "eval_rougeL": 0.5218799478770955,
2065
+ "eval_rougeLsum": 0.6332700294558067,
2066
+ "eval_runtime": 14.9089,
2067
+ "eval_samples_per_second": 0.671,
2068
+ "eval_steps_per_second": 0.335,
2069
+ "step": 20600
2070
+ },
2071
+ {
2072
+ "epoch": 2.37,
2073
+ "grad_norm": 0.39801183342933655,
2074
+ "learning_rate": 8.153359728829008e-05,
2075
+ "loss": 1.4177,
2076
+ "step": 20800
2077
+ },
2078
+ {
2079
+ "epoch": 2.37,
2080
+ "eval_bertscore": 0.7343758344650269,
2081
+ "eval_loss": 1.7737929821014404,
2082
+ "eval_rouge1": 0.6495678172205896,
2083
+ "eval_rouge2": 0.3505195734345703,
2084
+ "eval_rougeL": 0.5263025592812188,
2085
+ "eval_rougeLsum": 0.6390057749428748,
2086
+ "eval_runtime": 15.2148,
2087
+ "eval_samples_per_second": 0.657,
2088
+ "eval_steps_per_second": 0.329,
2089
+ "step": 20800
2090
+ },
2091
+ {
2092
+ "epoch": 2.39,
2093
+ "grad_norm": 0.36868759989738464,
2094
+ "learning_rate": 8.039422337425585e-05,
2095
+ "loss": 1.421,
2096
+ "step": 21000
2097
+ },
2098
+ {
2099
+ "epoch": 2.39,
2100
+ "eval_bertscore": 0.7333502173423767,
2101
+ "eval_loss": 1.7708820104599,
2102
+ "eval_rouge1": 0.656319412860679,
2103
+ "eval_rouge2": 0.3557406341135577,
2104
+ "eval_rougeL": 0.5293456110466322,
2105
+ "eval_rougeLsum": 0.6421819358163285,
2106
+ "eval_runtime": 14.9091,
2107
+ "eval_samples_per_second": 0.671,
2108
+ "eval_steps_per_second": 0.335,
2109
+ "step": 21000
2110
+ },
2111
+ {
2112
+ "epoch": 2.41,
2113
+ "grad_norm": 0.46111443638801575,
2114
+ "learning_rate": 7.925484946022162e-05,
2115
+ "loss": 1.4102,
2116
+ "step": 21200
2117
+ },
2118
+ {
2119
+ "epoch": 2.41,
2120
+ "eval_bertscore": 0.736262321472168,
2121
+ "eval_loss": 1.768972635269165,
2122
+ "eval_rouge1": 0.6582574071278393,
2123
+ "eval_rouge2": 0.3557625250443591,
2124
+ "eval_rougeL": 0.5322500342922363,
2125
+ "eval_rougeLsum": 0.646623827844921,
2126
+ "eval_runtime": 15.4088,
2127
+ "eval_samples_per_second": 0.649,
2128
+ "eval_steps_per_second": 0.324,
2129
+ "step": 21200
2130
+ },
2131
+ {
2132
+ "epoch": 2.44,
2133
+ "grad_norm": 0.41794517636299133,
2134
+ "learning_rate": 7.811547554618738e-05,
2135
+ "loss": 1.4231,
2136
+ "step": 21400
2137
+ },
2138
+ {
2139
+ "epoch": 2.44,
2140
+ "eval_bertscore": 0.7349900603294373,
2141
+ "eval_loss": 1.7673609256744385,
2142
+ "eval_rouge1": 0.6599777278993147,
2143
+ "eval_rouge2": 0.35744569380532043,
2144
+ "eval_rougeL": 0.5359850821835463,
2145
+ "eval_rougeLsum": 0.6469206354455653,
2146
+ "eval_runtime": 14.8837,
2147
+ "eval_samples_per_second": 0.672,
2148
+ "eval_steps_per_second": 0.336,
2149
+ "step": 21400
2150
+ },
2151
+ {
2152
+ "epoch": 2.46,
2153
+ "grad_norm": 0.3874039351940155,
2154
+ "learning_rate": 7.697610163215314e-05,
2155
+ "loss": 1.4158,
2156
+ "step": 21600
2157
+ },
2158
+ {
2159
+ "epoch": 2.46,
2160
+ "eval_bertscore": 0.7362676858901978,
2161
+ "eval_loss": 1.764347791671753,
2162
+ "eval_rouge1": 0.6576168971663054,
2163
+ "eval_rouge2": 0.36010190798950537,
2164
+ "eval_rougeL": 0.5365592740576962,
2165
+ "eval_rougeLsum": 0.6455601225938818,
2166
+ "eval_runtime": 15.4178,
2167
+ "eval_samples_per_second": 0.649,
2168
+ "eval_steps_per_second": 0.324,
2169
+ "step": 21600
2170
+ }
2171
+ ],
2172
+ "logging_steps": 200,
2173
+ "max_steps": 35112,
2174
+ "num_input_tokens_seen": 0,
2175
+ "num_train_epochs": 4,
2176
+ "save_steps": 800,
2177
+ "total_flos": 2.1880581377217454e+18,
2178
+ "train_batch_size": 2,
2179
+ "trial_name": null,
2180
+ "trial_params": null
2181
+ }
checkpoint-21600/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d576743d4294cfbcae212243377437f73cabbcded2df9da7f73e6e39ecb38f56
3
+ size 5048
checkpoint-22400/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: peft
3
+ base_model: unsloth/gemma-2b-bnb-4bit
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.10.0
checkpoint-22400/adapter_config.json ADDED
@@ -0,0 +1,34 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "unsloth/gemma-2b-bnb-4bit",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 32,
14
+ "lora_dropout": 0,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 64,
20
+ "rank_pattern": {},
21
+ "revision": "unsloth",
22
+ "target_modules": [
23
+ "v_proj",
24
+ "up_proj",
25
+ "gate_proj",
26
+ "o_proj",
27
+ "k_proj",
28
+ "down_proj",
29
+ "q_proj"
30
+ ],
31
+ "task_type": "CAUSAL_LM",
32
+ "use_dora": false,
33
+ "use_rslora": false
34
+ }
checkpoint-22400/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:cd6015a3bec35ad1dc604e30fb01a9c051ef9b3e36304464382ec41c027196bb
3
+ size 313820248
checkpoint-22400/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:51466a5ddd7196f688cac7aee47b26b078df13365d4372200c01a591729462c5
3
+ size 14244
checkpoint-22400/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:512b506129b7457fd633b55ef740589dea9c8726485f78ed74b0523c9944ff7f
3
+ size 1064