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distilbert-base-uncased__subj__train-8-1
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: 0.5488
- Accuracy: 0.791
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 |
---|---|---|---|---|
0.703 | 1.0 | 3 | 0.6906 | 0.5 |
0.666 | 2.0 | 6 | 0.6945 | 0.25 |
0.63 | 3.0 | 9 | 0.6885 | 0.5 |
0.588 | 4.0 | 12 | 0.6888 | 0.25 |
0.5181 | 5.0 | 15 | 0.6899 | 0.25 |
0.4508 | 6.0 | 18 | 0.6770 | 0.5 |
0.4025 | 7.0 | 21 | 0.6579 | 0.5 |
0.3361 | 8.0 | 24 | 0.6392 | 0.5 |
0.2919 | 9.0 | 27 | 0.6113 | 0.5 |
0.2151 | 10.0 | 30 | 0.5774 | 0.75 |
0.1728 | 11.0 | 33 | 0.5248 | 0.75 |
0.1313 | 12.0 | 36 | 0.4824 | 0.75 |
0.1046 | 13.0 | 39 | 0.4456 | 0.75 |
0.0858 | 14.0 | 42 | 0.4076 | 0.75 |
0.0679 | 15.0 | 45 | 0.3755 | 0.75 |
0.0485 | 16.0 | 48 | 0.3422 | 0.75 |
0.0416 | 17.0 | 51 | 0.3055 | 0.75 |
0.0358 | 18.0 | 54 | 0.2731 | 1.0 |
0.0277 | 19.0 | 57 | 0.2443 | 1.0 |
0.0234 | 20.0 | 60 | 0.2187 | 1.0 |
0.0223 | 21.0 | 63 | 0.1960 | 1.0 |
0.0187 | 22.0 | 66 | 0.1762 | 1.0 |
0.017 | 23.0 | 69 | 0.1629 | 1.0 |
0.0154 | 24.0 | 72 | 0.1543 | 1.0 |
0.0164 | 25.0 | 75 | 0.1476 | 1.0 |
0.0131 | 26.0 | 78 | 0.1423 | 1.0 |
0.0139 | 27.0 | 81 | 0.1387 | 1.0 |
0.0107 | 28.0 | 84 | 0.1360 | 1.0 |
0.0108 | 29.0 | 87 | 0.1331 | 1.0 |
0.0105 | 30.0 | 90 | 0.1308 | 1.0 |
0.0106 | 31.0 | 93 | 0.1276 | 1.0 |
0.0104 | 32.0 | 96 | 0.1267 | 1.0 |
0.0095 | 33.0 | 99 | 0.1255 | 1.0 |
0.0076 | 34.0 | 102 | 0.1243 | 1.0 |
0.0094 | 35.0 | 105 | 0.1235 | 1.0 |
0.0103 | 36.0 | 108 | 0.1228 | 1.0 |
0.0086 | 37.0 | 111 | 0.1231 | 1.0 |
0.0094 | 38.0 | 114 | 0.1236 | 1.0 |
0.0074 | 39.0 | 117 | 0.1240 | 1.0 |
0.0085 | 40.0 | 120 | 0.1246 | 1.0 |
0.0079 | 41.0 | 123 | 0.1253 | 1.0 |
0.0088 | 42.0 | 126 | 0.1248 | 1.0 |
0.0082 | 43.0 | 129 | 0.1244 | 1.0 |
0.0082 | 44.0 | 132 | 0.1234 | 1.0 |
0.0082 | 45.0 | 135 | 0.1223 | 1.0 |
0.0071 | 46.0 | 138 | 0.1212 | 1.0 |
0.0073 | 47.0 | 141 | 0.1208 | 1.0 |
0.0081 | 48.0 | 144 | 0.1205 | 1.0 |
0.0067 | 49.0 | 147 | 0.1202 | 1.0 |
0.0077 | 50.0 | 150 | 0.1202 | 1.0 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3