distilbert-base-uncased__subj__train-8-3
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3496
- Accuracy: 0.859
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.7136 | 1.0 | 3 | 0.6875 | 0.75 |
| 0.6702 | 2.0 | 6 | 0.6824 | 0.75 |
| 0.6456 | 3.0 | 9 | 0.6687 | 0.75 |
| 0.5934 | 4.0 | 12 | 0.6564 | 0.75 |
| 0.537 | 5.0 | 15 | 0.6428 | 0.75 |
| 0.4812 | 6.0 | 18 | 0.6180 | 0.75 |
| 0.4279 | 7.0 | 21 | 0.5864 | 0.75 |
| 0.3608 | 8.0 | 24 | 0.5540 | 0.75 |
| 0.3076 | 9.0 | 27 | 0.5012 | 1.0 |
| 0.2292 | 10.0 | 30 | 0.4497 | 1.0 |
| 0.1991 | 11.0 | 33 | 0.3945 | 1.0 |
| 0.1495 | 12.0 | 36 | 0.3483 | 1.0 |
| 0.1176 | 13.0 | 39 | 0.3061 | 1.0 |
| 0.0947 | 14.0 | 42 | 0.2683 | 1.0 |
| 0.0761 | 15.0 | 45 | 0.2295 | 1.0 |
| 0.0584 | 16.0 | 48 | 0.1996 | 1.0 |
| 0.0451 | 17.0 | 51 | 0.1739 | 1.0 |
| 0.0387 | 18.0 | 54 | 0.1521 | 1.0 |
| 0.0272 | 19.0 | 57 | 0.1333 | 1.0 |
| 0.0247 | 20.0 | 60 | 0.1171 | 1.0 |
| 0.0243 | 21.0 | 63 | 0.1044 | 1.0 |
| 0.0206 | 22.0 | 66 | 0.0943 | 1.0 |
| 0.0175 | 23.0 | 69 | 0.0859 | 1.0 |
| 0.0169 | 24.0 | 72 | 0.0799 | 1.0 |
| 0.0162 | 25.0 | 75 | 0.0746 | 1.0 |
| 0.0137 | 26.0 | 78 | 0.0705 | 1.0 |
| 0.0141 | 27.0 | 81 | 0.0674 | 1.0 |
| 0.0107 | 28.0 | 84 | 0.0654 | 1.0 |
| 0.0117 | 29.0 | 87 | 0.0634 | 1.0 |
| 0.0113 | 30.0 | 90 | 0.0617 | 1.0 |
| 0.0107 | 31.0 | 93 | 0.0599 | 1.0 |
| 0.0106 | 32.0 | 96 | 0.0585 | 1.0 |
| 0.0101 | 33.0 | 99 | 0.0568 | 1.0 |
| 0.0084 | 34.0 | 102 | 0.0553 | 1.0 |
| 0.0101 | 35.0 | 105 | 0.0539 | 1.0 |
| 0.0102 | 36.0 | 108 | 0.0529 | 1.0 |
| 0.009 | 37.0 | 111 | 0.0520 | 1.0 |
| 0.0092 | 38.0 | 114 | 0.0511 | 1.0 |
| 0.0073 | 39.0 | 117 | 0.0504 | 1.0 |
| 0.0081 | 40.0 | 120 | 0.0497 | 1.0 |
| 0.0079 | 41.0 | 123 | 0.0492 | 1.0 |
| 0.0092 | 42.0 | 126 | 0.0488 | 1.0 |
| 0.008 | 43.0 | 129 | 0.0483 | 1.0 |
| 0.0087 | 44.0 | 132 | 0.0479 | 1.0 |
| 0.009 | 45.0 | 135 | 0.0474 | 1.0 |
| 0.0076 | 46.0 | 138 | 0.0470 | 1.0 |
| 0.0075 | 47.0 | 141 | 0.0467 | 1.0 |
| 0.008 | 48.0 | 144 | 0.0465 | 1.0 |
| 0.0069 | 49.0 | 147 | 0.0464 | 1.0 |
| 0.0077 | 50.0 | 150 | 0.0464 | 1.0 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3
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