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my_awesome_wnut_model

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  1. README.md +16 -34
  2. config.json +39 -17
  3. model.safetensors +2 -2
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README.md CHANGED
@@ -1,7 +1,7 @@
1
  ---
2
  library_name: transformers
3
  license: apache-2.0
4
- base_model: sentence-transformers/all-MiniLM-L12-v2
5
  tags:
6
  - generated_from_trainer
7
  metrics:
@@ -19,13 +19,13 @@ should probably proofread and complete it, then remove this comment. -->
19
 
20
  # my_awesome_wnut_model
21
 
22
- This model is a fine-tuned version of [sentence-transformers/all-MiniLM-L12-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L12-v2) on the None dataset.
23
  It achieves the following results on the evaluation set:
24
- - Loss: 0.1343
25
- - Precision: 0.7732
26
- - Recall: 0.5806
27
- - F1: 0.6632
28
- - Accuracy: 0.9673
29
 
30
  ## Model description
31
 
@@ -45,42 +45,24 @@ More information needed
45
 
46
  The following hyperparameters were used during training:
47
  - learning_rate: 2e-05
48
- - train_batch_size: 64
49
- - eval_batch_size: 64
50
  - seed: 42
51
  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
52
  - lr_scheduler_type: linear
 
53
  - num_epochs: 50
54
 
55
  ### Training results
56
 
57
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
58
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
59
- | 0.2631 | 2.0 | 20 | 0.1800 | 0.0 | 0.0 | 0.0 | 0.9446 |
60
- | 0.1442 | 4.0 | 40 | 0.1659 | 0.0 | 0.0 | 0.0 | 0.9446 |
61
- | 0.1359 | 6.0 | 60 | 0.1506 | 1.0 | 0.1095 | 0.1974 | 0.9507 |
62
- | 0.1217 | 8.0 | 80 | 0.1376 | 0.7412 | 0.2513 | 0.3754 | 0.9537 |
63
- | 0.1076 | 10.0 | 100 | 0.1274 | 0.6996 | 0.5416 | 0.6106 | 0.9617 |
64
- | 0.0931 | 12.0 | 120 | 0.1195 | 0.7484 | 0.6114 | 0.6730 | 0.9671 |
65
- | 0.0852 | 14.0 | 140 | 0.1089 | 0.8770 | 0.4869 | 0.6261 | 0.9678 |
66
- | 0.0806 | 16.0 | 160 | 0.1107 | 0.8187 | 0.5896 | 0.6856 | 0.9700 |
67
- | 0.0742 | 18.0 | 180 | 0.1141 | 0.8289 | 0.5671 | 0.6735 | 0.9696 |
68
- | 0.0716 | 20.0 | 200 | 0.1154 | 0.8352 | 0.5551 | 0.6670 | 0.9693 |
69
- | 0.0651 | 22.0 | 220 | 0.1195 | 0.7721 | 0.5769 | 0.6604 | 0.9671 |
70
- | 0.063 | 24.0 | 240 | 0.1189 | 0.8154 | 0.5731 | 0.6731 | 0.9692 |
71
- | 0.0645 | 26.0 | 260 | 0.1189 | 0.8029 | 0.5746 | 0.6699 | 0.9686 |
72
- | 0.0629 | 28.0 | 280 | 0.1233 | 0.8114 | 0.5649 | 0.6661 | 0.9686 |
73
- | 0.0592 | 30.0 | 300 | 0.1278 | 0.7644 | 0.5791 | 0.6590 | 0.9668 |
74
- | 0.0589 | 32.0 | 320 | 0.1282 | 0.7603 | 0.5829 | 0.6599 | 0.9667 |
75
- | 0.0606 | 34.0 | 340 | 0.1259 | 0.8103 | 0.5671 | 0.6673 | 0.9687 |
76
- | 0.0603 | 36.0 | 360 | 0.1251 | 0.7821 | 0.5709 | 0.6600 | 0.9674 |
77
- | 0.0579 | 38.0 | 380 | 0.1330 | 0.7478 | 0.5806 | 0.6537 | 0.9659 |
78
- | 0.0571 | 40.0 | 400 | 0.1325 | 0.7703 | 0.5761 | 0.6592 | 0.9670 |
79
- | 0.0584 | 42.0 | 420 | 0.1320 | 0.7829 | 0.5761 | 0.6638 | 0.9677 |
80
- | 0.0559 | 44.0 | 440 | 0.1319 | 0.7969 | 0.5829 | 0.6733 | 0.9687 |
81
- | 0.0579 | 46.0 | 460 | 0.1333 | 0.8136 | 0.5761 | 0.6746 | 0.9692 |
82
- | 0.0561 | 48.0 | 480 | 0.1346 | 0.7615 | 0.5844 | 0.6613 | 0.9669 |
83
- | 0.0594 | 50.0 | 500 | 0.1343 | 0.7732 | 0.5806 | 0.6632 | 0.9673 |
84
 
85
 
86
  ### Framework versions
 
1
  ---
2
  library_name: transformers
3
  license: apache-2.0
4
+ base_model: answerdotai/ModernBERT-large
5
  tags:
6
  - generated_from_trainer
7
  metrics:
 
19
 
20
  # my_awesome_wnut_model
21
 
22
+ This model is a fine-tuned version of [answerdotai/ModernBERT-large](https://huggingface.co/answerdotai/ModernBERT-large) on the None dataset.
23
  It achieves the following results on the evaluation set:
24
+ - Loss: 0.5795
25
+ - Precision: 0.2438
26
+ - Recall: 0.6759
27
+ - F1: 0.3583
28
+ - Accuracy: 0.8634
29
 
30
  ## Model description
31
 
 
45
 
46
  The following hyperparameters were used during training:
47
  - learning_rate: 2e-05
48
+ - train_batch_size: 8
49
+ - eval_batch_size: 8
50
  - seed: 42
51
  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
52
  - lr_scheduler_type: linear
53
+ - lr_scheduler_warmup_steps: 10
54
  - num_epochs: 50
55
 
56
  ### Training results
57
 
58
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
59
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
60
+ | 1.5943 | 1.0 | 38 | 0.3653 | 0.1156 | 0.6069 | 0.1943 | 0.8489 |
61
+ | 1.5943 | 2.0 | 76 | 0.3859 | 0.2032 | 0.7034 | 0.3153 | 0.8691 |
62
+ | 0.2445 | 3.0 | 114 | 0.4085 | 0.2422 | 0.8069 | 0.3726 | 0.8679 |
63
+ | 0.2445 | 4.0 | 152 | 0.3778 | 0.2013 | 0.6345 | 0.3056 | 0.8733 |
64
+ | 0.2445 | 5.0 | 190 | 0.4417 | 0.2010 | 0.5448 | 0.2937 | 0.8755 |
65
+ | 0.0861 | 6.0 | 228 | 0.5795 | 0.2438 | 0.6759 | 0.3583 | 0.8634 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
66
 
67
 
68
  ### Framework versions
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@@ -1,33 +1,55 @@
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  "torch_dtype": "float32",
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30
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31
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32
- "vocab_size": 30522
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  }
 
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42
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45
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