gokuls commited on
Commit
e880ead
1 Parent(s): 70bd786

End of training

Browse files
Files changed (5) hide show
  1. README.md +6 -4
  2. all_results.json +21 -0
  3. eval_results.json +16 -0
  4. train_results.json +8 -0
  5. trainer_state.json +163 -0
README.md CHANGED
@@ -1,4 +1,6 @@
1
  ---
 
 
2
  base_model: gokuls/bert_12_layer_model_v1_complete_training_new_48
3
  tags:
4
  - generated_from_trainer
@@ -13,7 +15,7 @@ model-index:
13
  name: Text Classification
14
  type: text-classification
15
  dataset:
16
- name: glue
17
  type: glue
18
  config: mnli
19
  split: validation_matched
@@ -21,7 +23,7 @@ model-index:
21
  metrics:
22
  - name: Accuracy
23
  type: accuracy
24
- value: 0.31818644931227713
25
  ---
26
 
27
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -29,10 +31,10 @@ should probably proofread and complete it, then remove this comment. -->
29
 
30
  # hBERTv1_new_pretrain_48_ver2_mnli
31
 
32
- This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1_complete_training_new_48](https://huggingface.co/gokuls/bert_12_layer_model_v1_complete_training_new_48) on the glue dataset.
33
  It achieves the following results on the evaluation set:
34
  - Loss: 1.0986
35
- - Accuracy: 0.3182
36
 
37
  ## Model description
38
 
 
1
  ---
2
+ language:
3
+ - en
4
  base_model: gokuls/bert_12_layer_model_v1_complete_training_new_48
5
  tags:
6
  - generated_from_trainer
 
15
  name: Text Classification
16
  type: text-classification
17
  dataset:
18
+ name: GLUE MNLI
19
  type: glue
20
  config: mnli
21
  split: validation_matched
 
23
  metrics:
24
  - name: Accuracy
25
  type: accuracy
26
+ value: 0.3522172497965826
27
  ---
28
 
29
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
31
 
32
  # hBERTv1_new_pretrain_48_ver2_mnli
33
 
34
+ This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1_complete_training_new_48](https://huggingface.co/gokuls/bert_12_layer_model_v1_complete_training_new_48) on the GLUE MNLI dataset.
35
  It achieves the following results on the evaluation set:
36
  - Loss: 1.0986
37
+ - Accuracy: 0.3522
38
 
39
  ## Model description
40
 
all_results.json ADDED
@@ -0,0 +1,21 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "epoch": 9.0,
3
+ "epoch_mm": 9.0,
4
+ "eval_accuracy": 0.3544574630667346,
5
+ "eval_accuracy_mm": 0.3522172497965826,
6
+ "eval_loss": 1.0985641479492188,
7
+ "eval_loss_mm": 1.0985745191574097,
8
+ "eval_runtime": 21.5774,
9
+ "eval_runtime_mm": 21.611,
10
+ "eval_samples": 9815,
11
+ "eval_samples_mm": 9832,
12
+ "eval_samples_per_second": 454.875,
13
+ "eval_samples_per_second_mm": 454.953,
14
+ "eval_steps_per_second": 7.137,
15
+ "eval_steps_per_second_mm": 7.126,
16
+ "train_loss": 1.0989558399371198,
17
+ "train_runtime": 25003.8725,
18
+ "train_samples": 392702,
19
+ "train_samples_per_second": 235.585,
20
+ "train_steps_per_second": 3.681
21
+ }
eval_results.json ADDED
@@ -0,0 +1,16 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "epoch": 9.0,
3
+ "epoch_mm": 9.0,
4
+ "eval_accuracy": 0.3544574630667346,
5
+ "eval_accuracy_mm": 0.3522172497965826,
6
+ "eval_loss": 1.0985641479492188,
7
+ "eval_loss_mm": 1.0985745191574097,
8
+ "eval_runtime": 21.5774,
9
+ "eval_runtime_mm": 21.611,
10
+ "eval_samples": 9815,
11
+ "eval_samples_mm": 9832,
12
+ "eval_samples_per_second": 454.875,
13
+ "eval_samples_per_second_mm": 454.953,
14
+ "eval_steps_per_second": 7.137,
15
+ "eval_steps_per_second_mm": 7.126
16
+ }
train_results.json ADDED
@@ -0,0 +1,8 @@
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "epoch": 9.0,
3
+ "train_loss": 1.0989558399371198,
4
+ "train_runtime": 25003.8725,
5
+ "train_samples": 392702,
6
+ "train_samples_per_second": 235.585,
7
+ "train_steps_per_second": 3.681
8
+ }
trainer_state.json ADDED
@@ -0,0 +1,163 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": 1.0985641479492188,
3
+ "best_model_checkpoint": "hBERTv1_new_pretrain_48_ver2_mnli/checkpoint-24544",
4
+ "epoch": 9.0,
5
+ "eval_steps": 500,
6
+ "global_step": 55224,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 1.0,
13
+ "learning_rate": 3.733333333333334e-05,
14
+ "loss": 1.1013,
15
+ "step": 6136
16
+ },
17
+ {
18
+ "epoch": 1.0,
19
+ "eval_accuracy": 0.31818644931227713,
20
+ "eval_loss": 1.0990490913391113,
21
+ "eval_runtime": 21.8244,
22
+ "eval_samples_per_second": 449.726,
23
+ "eval_steps_per_second": 7.056,
24
+ "step": 6136
25
+ },
26
+ {
27
+ "epoch": 2.0,
28
+ "learning_rate": 3.466666666666667e-05,
29
+ "loss": 1.0988,
30
+ "step": 12272
31
+ },
32
+ {
33
+ "epoch": 2.0,
34
+ "eval_accuracy": 0.31818644931227713,
35
+ "eval_loss": 1.099389910697937,
36
+ "eval_runtime": 21.8009,
37
+ "eval_samples_per_second": 450.21,
38
+ "eval_steps_per_second": 7.064,
39
+ "step": 12272
40
+ },
41
+ {
42
+ "epoch": 3.0,
43
+ "learning_rate": 3.2000000000000005e-05,
44
+ "loss": 1.0987,
45
+ "step": 18408
46
+ },
47
+ {
48
+ "epoch": 3.0,
49
+ "eval_accuracy": 0.31818644931227713,
50
+ "eval_loss": 1.0986260175704956,
51
+ "eval_runtime": 21.7566,
52
+ "eval_samples_per_second": 451.128,
53
+ "eval_steps_per_second": 7.078,
54
+ "step": 18408
55
+ },
56
+ {
57
+ "epoch": 4.0,
58
+ "learning_rate": 2.9333333333333333e-05,
59
+ "loss": 1.0986,
60
+ "step": 24544
61
+ },
62
+ {
63
+ "epoch": 4.0,
64
+ "eval_accuracy": 0.3544574630667346,
65
+ "eval_loss": 1.0985641479492188,
66
+ "eval_runtime": 21.6777,
67
+ "eval_samples_per_second": 452.769,
68
+ "eval_steps_per_second": 7.104,
69
+ "step": 24544
70
+ },
71
+ {
72
+ "epoch": 5.0,
73
+ "learning_rate": 2.6666666666666667e-05,
74
+ "loss": 1.0986,
75
+ "step": 30680
76
+ },
77
+ {
78
+ "epoch": 5.0,
79
+ "eval_accuracy": 0.3544574630667346,
80
+ "eval_loss": 1.0985902547836304,
81
+ "eval_runtime": 21.7473,
82
+ "eval_samples_per_second": 451.321,
83
+ "eval_steps_per_second": 7.081,
84
+ "step": 30680
85
+ },
86
+ {
87
+ "epoch": 6.0,
88
+ "learning_rate": 2.4e-05,
89
+ "loss": 1.0986,
90
+ "step": 36816
91
+ },
92
+ {
93
+ "epoch": 6.0,
94
+ "eval_accuracy": 0.3273560876209883,
95
+ "eval_loss": 1.0986045598983765,
96
+ "eval_runtime": 21.8778,
97
+ "eval_samples_per_second": 448.627,
98
+ "eval_steps_per_second": 7.039,
99
+ "step": 36816
100
+ },
101
+ {
102
+ "epoch": 7.0,
103
+ "learning_rate": 2.1333333333333335e-05,
104
+ "loss": 1.0986,
105
+ "step": 42952
106
+ },
107
+ {
108
+ "epoch": 7.0,
109
+ "eval_accuracy": 0.3544574630667346,
110
+ "eval_loss": 1.098606824874878,
111
+ "eval_runtime": 21.6702,
112
+ "eval_samples_per_second": 452.927,
113
+ "eval_steps_per_second": 7.107,
114
+ "step": 42952
115
+ },
116
+ {
117
+ "epoch": 8.0,
118
+ "learning_rate": 1.866666666666667e-05,
119
+ "loss": 1.0986,
120
+ "step": 49088
121
+ },
122
+ {
123
+ "epoch": 8.0,
124
+ "eval_accuracy": 0.3544574630667346,
125
+ "eval_loss": 1.0986090898513794,
126
+ "eval_runtime": 21.6888,
127
+ "eval_samples_per_second": 452.539,
128
+ "eval_steps_per_second": 7.1,
129
+ "step": 49088
130
+ },
131
+ {
132
+ "epoch": 9.0,
133
+ "learning_rate": 1.6000000000000003e-05,
134
+ "loss": 1.0986,
135
+ "step": 55224
136
+ },
137
+ {
138
+ "epoch": 9.0,
139
+ "eval_accuracy": 0.31818644931227713,
140
+ "eval_loss": 1.098615050315857,
141
+ "eval_runtime": 21.6696,
142
+ "eval_samples_per_second": 452.938,
143
+ "eval_steps_per_second": 7.107,
144
+ "step": 55224
145
+ },
146
+ {
147
+ "epoch": 9.0,
148
+ "step": 55224,
149
+ "total_flos": 5.2342526347680154e+17,
150
+ "train_loss": 1.0989558399371198,
151
+ "train_runtime": 25003.8725,
152
+ "train_samples_per_second": 235.585,
153
+ "train_steps_per_second": 3.681
154
+ }
155
+ ],
156
+ "logging_steps": 1,
157
+ "max_steps": 92040,
158
+ "num_train_epochs": 15,
159
+ "save_steps": 500,
160
+ "total_flos": 5.2342526347680154e+17,
161
+ "trial_name": null,
162
+ "trial_params": null
163
+ }