bert_base_lda_100_v1_book
This model is a fine-tuned version of on the gokulsrinivasagan/processed_book_corpus-ld-100 dataset. It achieves the following results on the evaluation set:
- Loss: 4.4757
- Accuracy: 0.7551
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 |
|---|---|---|---|---|
| 9.5861 | 0.4215 | 10000 | 9.3593 | 0.1636 |
| 9.2311 | 0.8431 | 20000 | 9.0701 | 0.1641 |
| 9.1362 | 1.2646 | 30000 | 8.9889 | 0.1662 |
| 6.984 | 1.6861 | 40000 | 6.4486 | 0.4683 |
| 5.8878 | 2.1077 | 50000 | 5.5436 | 0.5941 |
| 5.6092 | 2.5292 | 60000 | 5.2862 | 0.6336 |
| 5.4567 | 2.9507 | 70000 | 5.1556 | 0.6531 |
| 5.3612 | 3.3723 | 80000 | 5.0665 | 0.6665 |
| 5.2881 | 3.7938 | 90000 | 4.9997 | 0.6763 |
| 5.2269 | 4.2153 | 100000 | 4.9488 | 0.6834 |
| 5.1854 | 4.6369 | 110000 | 4.9087 | 0.6889 |
| 5.1474 | 5.0584 | 120000 | 4.8727 | 0.6944 |
| 5.1144 | 5.4799 | 130000 | 4.8404 | 0.6990 |
| 5.0914 | 5.9014 | 140000 | 4.8134 | 0.7026 |
| 5.0579 | 6.3230 | 150000 | 4.7935 | 0.7058 |
| 5.044 | 6.7445 | 160000 | 4.7736 | 0.7089 |
| 5.0124 | 7.1660 | 170000 | 4.7533 | 0.7124 |
| 4.9997 | 7.5876 | 180000 | 4.7431 | 0.7140 |
| 4.9809 | 8.0091 | 190000 | 4.7224 | 0.7163 |
| 4.9674 | 8.4306 | 200000 | 4.7087 | 0.7189 |
| 4.9526 | 8.8522 | 210000 | 4.6976 | 0.7206 |
| 4.9422 | 9.2737 | 220000 | 4.6848 | 0.7224 |
| 4.9232 | 9.6952 | 230000 | 4.6721 | 0.7242 |
| 4.9073 | 10.1168 | 240000 | 4.6646 | 0.7261 |
| 4.9072 | 10.5383 | 250000 | 4.6502 | 0.7276 |
| 4.8916 | 10.9598 | 260000 | 4.6415 | 0.7290 |
| 4.8805 | 11.3814 | 270000 | 4.6341 | 0.7301 |
| 4.8775 | 11.8029 | 280000 | 4.6231 | 0.7318 |
| 4.86 | 12.2244 | 290000 | 4.6168 | 0.7330 |
| 4.8539 | 12.6460 | 300000 | 4.6066 | 0.7346 |
| 4.8416 | 13.0675 | 310000 | 4.5990 | 0.7359 |
| 4.8371 | 13.4890 | 320000 | 4.5932 | 0.7366 |
| 4.8312 | 13.9106 | 330000 | 4.5877 | 0.7373 |
| 4.8264 | 14.3321 | 340000 | 4.5786 | 0.7392 |
| 4.8157 | 14.7536 | 350000 | 4.5722 | 0.7398 |
| 4.8097 | 15.1751 | 360000 | 4.5686 | 0.7404 |
| 4.8045 | 15.5967 | 370000 | 4.5596 | 0.7416 |
| 4.7951 | 16.0182 | 380000 | 4.5546 | 0.7427 |
| 4.7906 | 16.4397 | 390000 | 4.5487 | 0.7434 |
| 4.7858 | 16.8613 | 400000 | 4.5452 | 0.7441 |
| 4.7798 | 17.2828 | 410000 | 4.5381 | 0.7452 |
| 4.7725 | 17.7043 | 420000 | 4.5330 | 0.7461 |
| 4.7628 | 18.1259 | 430000 | 4.5300 | 0.7466 |
| 4.7584 | 18.5474 | 440000 | 4.5251 | 0.7472 |
| 4.7573 | 18.9689 | 450000 | 4.5193 | 0.7483 |
| 4.7502 | 19.3905 | 460000 | 4.5154 | 0.7488 |
| 4.7482 | 19.8120 | 470000 | 4.5109 | 0.7496 |
| 4.738 | 20.2335 | 480000 | 4.5065 | 0.7502 |
| 4.7328 | 20.6551 | 490000 | 4.5021 | 0.7509 |
| 4.7289 | 21.0766 | 500000 | 4.4975 | 0.7515 |
| 4.7235 | 21.4981 | 510000 | 4.4950 | 0.7521 |
| 4.7191 | 21.9197 | 520000 | 4.4923 | 0.7525 |
| 4.7191 | 22.3412 | 530000 | 4.4891 | 0.7530 |
| 4.714 | 22.7627 | 540000 | 4.4877 | 0.7534 |
| 4.714 | 23.1843 | 550000 | 4.4832 | 0.7539 |
| 4.7086 | 23.6058 | 560000 | 4.4800 | 0.7544 |
| 4.7055 | 24.0273 | 570000 | 4.4785 | 0.7547 |
| 4.7024 | 24.4488 | 580000 | 4.4747 | 0.7552 |
| 4.6993 | 24.8704 | 590000 | 4.4753 | 0.7550 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3