bert_base_lda_20_v1_book
This model is a fine-tuned version of on the gokulsrinivasagan/processed_book_corpus-ld-20 dataset. It achieves the following results on the evaluation set:
- Loss: 3.4102
- Accuracy: 0.7596
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: 96
- eval_batch_size: 96
- seed: 10
- optimizer: Use 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 |
|---|---|---|---|---|
| 8.1966 | 0.4215 | 10000 | 8.0049 | 0.1640 |
| 8.0473 | 0.8431 | 20000 | 7.8939 | 0.1656 |
| 6.9645 | 1.2646 | 30000 | 6.4681 | 0.3352 |
| 4.9295 | 1.6861 | 40000 | 4.5709 | 0.5785 |
| 4.5377 | 2.1077 | 50000 | 4.2350 | 0.6289 |
| 4.3734 | 2.5292 | 60000 | 4.0854 | 0.6527 |
| 4.2676 | 2.9507 | 70000 | 3.9894 | 0.6667 |
| 4.1937 | 3.3723 | 80000 | 3.9218 | 0.6772 |
| 4.1383 | 3.7938 | 90000 | 3.8696 | 0.6855 |
| 4.0903 | 4.2153 | 100000 | 3.8305 | 0.6918 |
| 4.0556 | 4.6369 | 110000 | 3.7986 | 0.6968 |
| 4.0202 | 5.0584 | 120000 | 3.7627 | 0.7016 |
| 3.9954 | 5.4799 | 130000 | 3.7404 | 0.7054 |
| 3.9765 | 5.9014 | 140000 | 3.7157 | 0.7093 |
| 3.9475 | 6.3230 | 150000 | 3.6981 | 0.7121 |
| 3.934 | 6.7445 | 160000 | 3.6797 | 0.7152 |
| 3.9051 | 7.1660 | 170000 | 3.6612 | 0.7182 |
| 3.8964 | 7.5876 | 180000 | 3.6575 | 0.7176 |
| 3.8816 | 8.0091 | 190000 | 3.6411 | 0.7198 |
| 3.866 | 8.4306 | 200000 | 3.6233 | 0.7243 |
| 3.8514 | 8.8522 | 210000 | 3.6129 | 0.7259 |
| 3.8458 | 9.2737 | 220000 | 3.6029 | 0.7278 |
| 3.8295 | 9.6952 | 230000 | 3.5904 | 0.7293 |
| 3.8176 | 10.1168 | 240000 | 3.5856 | 0.7307 |
| 3.8131 | 10.5383 | 250000 | 3.5751 | 0.7319 |
| 3.7999 | 10.9598 | 260000 | 3.5652 | 0.7337 |
| 3.7893 | 11.3814 | 270000 | 3.5577 | 0.7348 |
| 3.7844 | 11.8029 | 280000 | 3.5480 | 0.7366 |
| 3.7698 | 12.2244 | 290000 | 3.5411 | 0.7377 |
| 3.7647 | 12.6460 | 300000 | 3.5322 | 0.7390 |
| 3.752 | 13.0675 | 310000 | 3.5254 | 0.7403 |
| 3.7505 | 13.4890 | 320000 | 3.5207 | 0.7412 |
| 3.7444 | 13.9106 | 330000 | 3.5145 | 0.7421 |
| 3.737 | 14.3321 | 340000 | 3.5068 | 0.7435 |
| 3.728 | 14.7536 | 350000 | 3.5010 | 0.7442 |
| 3.7219 | 15.1751 | 360000 | 3.4959 | 0.7450 |
| 3.7175 | 15.5967 | 370000 | 3.4885 | 0.7461 |
| 3.7095 | 16.0182 | 380000 | 3.4826 | 0.7472 |
| 3.7041 | 16.4397 | 390000 | 3.4774 | 0.7481 |
| 3.6965 | 16.8613 | 400000 | 3.4750 | 0.7488 |
| 3.6936 | 17.2828 | 410000 | 3.4675 | 0.7496 |
| 3.6885 | 17.7043 | 420000 | 3.4642 | 0.7505 |
| 3.679 | 18.1259 | 430000 | 3.4608 | 0.7512 |
| 3.6735 | 18.5474 | 440000 | 3.4564 | 0.7517 |
| 3.6726 | 18.9689 | 450000 | 3.4499 | 0.7528 |
| 3.6668 | 19.3905 | 460000 | 3.4468 | 0.7534 |
| 3.663 | 19.8120 | 470000 | 3.4422 | 0.7541 |
| 3.656 | 20.2335 | 480000 | 3.4387 | 0.7546 |
| 3.6499 | 20.6551 | 490000 | 3.4352 | 0.7554 |
| 3.6462 | 21.0766 | 500000 | 3.4307 | 0.7559 |
| 3.6423 | 21.4981 | 510000 | 3.4273 | 0.7566 |
| 3.6374 | 21.9197 | 520000 | 3.4252 | 0.7569 |
| 3.6389 | 22.3412 | 530000 | 3.4225 | 0.7574 |
| 3.6316 | 22.7627 | 540000 | 3.4215 | 0.7577 |
| 3.6323 | 23.1843 | 550000 | 3.4175 | 0.7582 |
| 3.6287 | 23.6058 | 560000 | 3.4146 | 0.7589 |
| 3.623 | 24.0273 | 570000 | 3.4132 | 0.7591 |
| 3.6224 | 24.4488 | 580000 | 3.4097 | 0.7595 |
| 3.6193 | 24.8704 | 590000 | 3.4098 | 0.7595 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3