Hugging Face's logo

christinacdl
/
xlm-roberta-large_ALL_BCE_new_data_multihead_19_shuffled_special_tokens_final

Transformers
Safetensors
roberta
Generated from Trainer
Inference Endpoints
Model card Files Community
christinacdl commited on
Commit
b719313
•
1 Parent(s): f2a9220

End of training

Browse files
Files changed (1) hide show
  1. README.md +119 -0
README.md ADDED
@@ -0,0 +1,119 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: mit
3
+ base_model: xlm-roberta-large
4
+ tags:
5
+ - generated_from_trainer
6
+ model-index:
7
+ - name: xlm-roberta-large_ALL_BCE_new_data_multihead_19_shuffled_special_tokens_final
8
+ results: []
9
+ ---
10
+
11
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
12
+ should probably proofread and complete it, then remove this comment. -->
13
+
14
+ # xlm-roberta-large_ALL_BCE_new_data_multihead_19_shuffled_special_tokens_final
15
+
16
+ This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on the None dataset.
17
+ It achieves the following results on the evaluation set:
18
+ - Loss: 1.4169
19
+ - F1 Macro 0.1: 0.0608
20
+ - F1 Macro 0.15: 0.0628
21
+ - F1 Macro 0.2: 0.0639
22
+ - F1 Macro 0.25: 0.0677
23
+ - F1 Macro 0.3: 0.0681
24
+ - F1 Macro 0.35: 0.0723
25
+ - F1 Macro 0.4: 0.0790
26
+ - F1 Macro 0.45: 0.0818
27
+ - F1 Macro 0.5: 0.0874
28
+ - F1 Macro 0.55: 0.0904
29
+ - F1 Macro 0.6: 0.0771
30
+ - F1 Macro 0.65: 0.0611
31
+ - F1 Macro 0.7: 0.0421
32
+ - F1 Macro 0.75: 0.0235
33
+ - F1 Macro 0.8: 0.0
34
+ - F1 Macro 0.85: 0.0
35
+ - F1 Macro 0.9: 0.0
36
+ - F1 Macro 0.95: 0.0
37
+ - Threshold 0: 0.45
38
+ - Threshold 1: 0.5
39
+ - Threshold 2: 0.7
40
+ - Threshold 3: 0.35
41
+ - Threshold 4: 0.6
42
+ - Threshold 5: 0.65
43
+ - Threshold 6: 0.55
44
+ - Threshold 7: 0.45
45
+ - Threshold 8: 0.55
46
+ - Threshold 9: 0.5
47
+ - Threshold 10: 0.5
48
+ - Threshold 11: 0.6
49
+ - Threshold 12: 0.4
50
+ - Threshold 13: 0.1
51
+ - Threshold 14: 0.45
52
+ - Threshold 15: 0.55
53
+ - Threshold 16: 0.55
54
+ - Threshold 17: 0.5
55
+ - Threshold 18: 0.35
56
+ - 0: 0.0476
57
+ - 1: 0.0951
58
+ - 2: 0.1069
59
+ - 3: 0.0416
60
+ - 4: 0.1579
61
+ - 5: 0.1767
62
+ - 6: 0.1486
63
+ - 7: 0.0558
64
+ - 8: 0.0742
65
+ - 9: 0.2208
66
+ - 10: 0.0532
67
+ - 11: 0.1499
68
+ - 12: 0.0799
69
+ - 13: 0.0095
70
+ - 14: 0.0968
71
+ - 15: 0.0679
72
+ - 16: 0.1100
73
+ - 17: 0.0621
74
+ - 18: 0.0296
75
+ - Max F1: 0.0904
76
+ - Mean F1: 0.0939
77
+
78
+ ## Model description
79
+
80
+ More information needed
81
+
82
+ ## Intended uses & limitations
83
+
84
+ More information needed
85
+
86
+ ## Training and evaluation data
87
+
88
+ More information needed
89
+
90
+ ## Training procedure
91
+
92
+ ### Training hyperparameters
93
+
94
+ The following hyperparameters were used during training:
95
+ - learning_rate: 5e-06
96
+ - train_batch_size: 8
97
+ - eval_batch_size: 8
98
+ - seed: 2024
99
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
100
+ - lr_scheduler_type: linear
101
+ - lr_scheduler_warmup_ratio: 0.1
102
+ - num_epochs: 3
103
+ - mixed_precision_training: Native AMP
104
+
105
+ ### Training results
106
+
107
+ | Training Loss | Epoch | Step | Validation Loss | F1 Macro 0.1 | F1 Macro 0.15 | F1 Macro 0.2 | F1 Macro 0.25 | F1 Macro 0.3 | F1 Macro 0.35 | F1 Macro 0.4 | F1 Macro 0.45 | F1 Macro 0.5 | F1 Macro 0.55 | F1 Macro 0.6 | F1 Macro 0.65 | F1 Macro 0.7 | F1 Macro 0.75 | F1 Macro 0.8 | F1 Macro 0.85 | F1 Macro 0.9 | F1 Macro 0.95 | Threshold 0 | Threshold 1 | Threshold 2 | Threshold 3 | Threshold 4 | Threshold 5 | Threshold 6 | Threshold 7 | Threshold 8 | Threshold 9 | Threshold 10 | Threshold 11 | Threshold 12 | Threshold 13 | Threshold 14 | Threshold 15 | Threshold 16 | Threshold 17 | Threshold 18 | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | Max F1 | Mean F1 |
108
+ |:-------------:|:-----:|:-----:|:---------------:|:------------:|:-------------:|:------------:|:-------------:|:------------:|:-------------:|:------------:|:-------------:|:------------:|:-------------:|:------------:|:-------------:|:------------:|:-------------:|:------------:|:-------------:|:------------:|:-------------:|:-----------:|:-----------:|:-----------:|:-----------:|:-----------:|:-----------:|:-----------:|:-----------:|:-----------:|:-----------:|:------------:|:------------:|:------------:|:------------:|:------------:|:------------:|:------------:|:------------:|:------------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:-------:|
109
+ | 1.4193 | 1.0 | 7458 | 1.4534 | 0.0606 | 0.0634 | 0.0648 | 0.0667 | 0.0689 | 0.0718 | 0.0765 | 0.0771 | 0.0811 | 0.0839 | 0.0856 | 0.0772 | 0.0562 | 0.0434 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4 | 0.55 | 0.6 | 0.3 | 0.55 | 0.7 | 0.55 | 0.55 | 0.6 | 0.5 | 0.4 | 0.6 | 0.6 | 0.1 | 0.5 | 0.55 | 0.55 | 0.5 | 0.35 | 0.0376 | 0.0951 | 0.1069 | 0.0416 | 0.1579 | 0.1767 | 0.1486 | 0.0558 | 0.0742 | 0.2208 | 0.0532 | 0.1499 | 0.0799 | 0.0095 | 0.0968 | 0.0655 | 0.1053 | 0.0621 | 0.0296 | 0.0856 | 0.0930 |
110
+ | 1.4423 | 2.0 | 14916 | 1.4217 | 0.0608 | 0.0627 | 0.0641 | 0.0673 | 0.0693 | 0.0732 | 0.0783 | 0.0835 | 0.0829 | 0.0861 | 0.0793 | 0.0621 | 0.0363 | 0.0093 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6 | 0.45 | 0.65 | 0.35 | 0.5 | 0.65 | 0.55 | 0.55 | 0.6 | 0.55 | 0.25 | 0.55 | 0.45 | 0.15 | 0.45 | 0.55 | 0.5 | 0.55 | 0.35 | 0.0476 | 0.0951 | 0.1069 | 0.0416 | 0.1569 | 0.1767 | 0.1486 | 0.0538 | 0.0742 | 0.2204 | 0.0520 | 0.1455 | 0.0799 | 0.0095 | 0.0968 | 0.0679 | 0.1100 | 0.0621 | 0.0270 | 0.0861 | 0.0933 |
111
+ | 1.4186 | 3.0 | 22374 | 1.4169 | 0.0608 | 0.0628 | 0.0639 | 0.0677 | 0.0681 | 0.0723 | 0.0790 | 0.0818 | 0.0874 | 0.0904 | 0.0771 | 0.0611 | 0.0421 | 0.0235 | 0.0 | 0.0 | 0.0 | 0.0 | 0.45 | 0.5 | 0.7 | 0.35 | 0.6 | 0.65 | 0.55 | 0.45 | 0.55 | 0.5 | 0.5 | 0.6 | 0.4 | 0.1 | 0.45 | 0.55 | 0.55 | 0.5 | 0.35 | 0.0476 | 0.0951 | 0.1069 | 0.0416 | 0.1579 | 0.1767 | 0.1486 | 0.0558 | 0.0742 | 0.2208 | 0.0532 | 0.1499 | 0.0799 | 0.0095 | 0.0968 | 0.0679 | 0.1100 | 0.0621 | 0.0296 | 0.0904 | 0.0939 |
112
+
113
+
114
+ ### Framework versions
115
+
116
+ - Transformers 4.36.1
117
+ - Pytorch 2.1.0+cu121
118
+ - Datasets 2.13.1
119
+ - Tokenizers 0.15.0