distilbert_base_train_book
This model is a fine-tuned version of distilbert-base-uncased on the gokulsrinivasagan/processed_book_corpus-ld dataset. It achieves the following results on the evaluation set:
- Loss: 1.2047
- Accuracy: 0.7295
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: 0.0001
- train_batch_size: 160
- eval_batch_size: 160
- seed: 10
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10000
- num_epochs: 25
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 5.6039 | 0.7025 | 10000 | 5.4506 | 0.1653 |
| 4.4684 | 1.4051 | 20000 | 3.7450 | 0.3849 |
| 2.3547 | 2.1076 | 30000 | 2.0441 | 0.5926 |
| 2.0785 | 2.8102 | 40000 | 1.7986 | 0.6309 |
| 1.938 | 3.5127 | 50000 | 1.6650 | 0.6520 |
| 1.8476 | 4.2153 | 60000 | 1.5862 | 0.6648 |
| 1.7905 | 4.9178 | 70000 | 1.5281 | 0.6746 |
| 1.74 | 5.6203 | 80000 | 1.4845 | 0.6815 |
| 1.7042 | 6.3229 | 90000 | 1.4543 | 0.6868 |
| 1.6725 | 7.0254 | 100000 | 1.4226 | 0.6917 |
| 1.6516 | 7.7280 | 110000 | 1.4016 | 0.6957 |
| 1.6269 | 8.4305 | 120000 | 1.3791 | 0.6991 |
| 1.6032 | 9.1331 | 130000 | 1.3647 | 0.7016 |
| 1.5903 | 9.8356 | 140000 | 1.3465 | 0.7051 |
| 1.5759 | 10.5381 | 150000 | 1.3326 | 0.7074 |
| 1.5641 | 11.2407 | 160000 | 1.3235 | 0.7090 |
| 1.5487 | 11.9432 | 170000 | 1.3103 | 0.7110 |
| 1.5384 | 12.6458 | 180000 | 1.2964 | 0.7133 |
| 1.527 | 13.3483 | 190000 | 1.2920 | 0.7144 |
| 1.5186 | 14.0509 | 200000 | 1.2808 | 0.7160 |
| 1.5086 | 14.7534 | 210000 | 1.2729 | 0.7174 |
| 1.4991 | 15.4560 | 220000 | 1.2637 | 0.7191 |
| 1.4936 | 16.1585 | 230000 | 1.2589 | 0.7198 |
| 1.4843 | 16.8610 | 240000 | 1.2534 | 0.7209 |
| 1.4763 | 17.5636 | 250000 | 1.2467 | 0.7219 |
| 1.4701 | 18.2661 | 260000 | 1.2408 | 0.7230 |
| 1.4668 | 18.9687 | 270000 | 1.2353 | 0.7240 |
| 1.458 | 19.6712 | 280000 | 1.2307 | 0.7249 |
| 1.4547 | 20.3738 | 290000 | 1.2251 | 0.7258 |
| 1.4466 | 21.0763 | 300000 | 1.2207 | 0.7266 |
| 1.4446 | 21.7788 | 310000 | 1.2153 | 0.7275 |
| 1.4375 | 22.4814 | 320000 | 1.2119 | 0.7281 |
| 1.4343 | 23.1839 | 330000 | 1.2086 | 0.7286 |
| 1.4325 | 23.8865 | 340000 | 1.2057 | 0.7293 |
| 1.4294 | 24.5890 | 350000 | 1.2024 | 0.7297 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.2.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.1