distilbert_lda_50_v1_book
This model is a fine-tuned version of on the gokulsrinivasagan/processed_book_corpus-ld-50 dataset. It achieves the following results on the evaluation set:
- Loss: 4.1487
- Accuracy: 0.7281
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 |
|---|---|---|---|---|
| 8.9162 | 0.4215 | 10000 | 8.5853 | 0.1955 |
| 5.7575 | 0.8431 | 20000 | 5.3762 | 0.5702 |
| 5.3383 | 1.2646 | 30000 | 5.0020 | 0.6136 |
| 5.1543 | 1.6861 | 40000 | 4.8293 | 0.6350 |
| 5.0355 | 2.1077 | 50000 | 4.7268 | 0.6473 |
| 4.9536 | 2.5292 | 60000 | 4.6440 | 0.6583 |
| 4.8934 | 2.9507 | 70000 | 4.5936 | 0.6648 |
| 4.8459 | 3.3723 | 80000 | 4.5508 | 0.6706 |
| 4.8083 | 3.7938 | 90000 | 4.5127 | 0.6758 |
| 4.7736 | 4.2153 | 100000 | 4.4858 | 0.6791 |
| 4.7514 | 4.6369 | 110000 | 4.4608 | 0.6827 |
| 4.7242 | 5.0584 | 120000 | 4.4364 | 0.6861 |
| 4.7039 | 5.4799 | 130000 | 4.4180 | 0.6886 |
| 4.6926 | 5.9014 | 140000 | 4.3993 | 0.6911 |
| 4.6677 | 6.3230 | 150000 | 4.3836 | 0.6933 |
| 4.6595 | 6.7445 | 160000 | 4.3707 | 0.6953 |
| 4.6349 | 7.1660 | 170000 | 4.3575 | 0.6975 |
| 4.6275 | 7.5876 | 180000 | 4.3497 | 0.6983 |
| 4.6149 | 8.0091 | 190000 | 4.3355 | 0.7002 |
| 4.6043 | 8.4306 | 200000 | 4.3248 | 0.7019 |
| 4.5925 | 8.8522 | 210000 | 4.3177 | 0.7030 |
| 4.586 | 9.2737 | 220000 | 4.3079 | 0.7043 |
| 4.5691 | 9.6952 | 230000 | 4.2980 | 0.7058 |
| 4.5581 | 10.1168 | 240000 | 4.2940 | 0.7070 |
| 4.5611 | 10.5383 | 250000 | 4.2824 | 0.7081 |
| 4.5492 | 10.9598 | 260000 | 4.2768 | 0.7090 |
| 4.5384 | 11.3814 | 270000 | 4.2734 | 0.7095 |
| 4.5396 | 11.8029 | 280000 | 4.2642 | 0.7106 |
| 4.5237 | 12.2244 | 290000 | 4.2593 | 0.7117 |
| 4.5205 | 12.6460 | 300000 | 4.2518 | 0.7127 |
| 4.5105 | 13.0675 | 310000 | 4.2450 | 0.7138 |
| 4.5085 | 13.4890 | 320000 | 4.2409 | 0.7144 |
| 4.5037 | 13.9106 | 330000 | 4.2371 | 0.7149 |
| 4.5007 | 14.3321 | 340000 | 4.2299 | 0.7161 |
| 4.4931 | 14.7536 | 350000 | 4.2254 | 0.7165 |
| 4.4864 | 15.1751 | 360000 | 4.2212 | 0.7171 |
| 4.4842 | 15.5967 | 370000 | 4.2133 | 0.7182 |
| 4.4762 | 16.0182 | 380000 | 4.2096 | 0.7190 |
| 4.471 | 16.4397 | 390000 | 4.2059 | 0.7194 |
| 4.467 | 16.8613 | 400000 | 4.2037 | 0.7198 |
| 4.4651 | 17.2828 | 410000 | 4.1972 | 0.7208 |
| 4.4579 | 17.7043 | 420000 | 4.1947 | 0.7213 |
| 4.4519 | 18.1259 | 430000 | 4.1922 | 0.7217 |
| 4.4457 | 18.5474 | 440000 | 4.1885 | 0.7220 |
| 4.4465 | 18.9689 | 450000 | 4.1830 | 0.7230 |
| 4.441 | 19.3905 | 460000 | 4.1797 | 0.7234 |
| 4.4385 | 19.8120 | 470000 | 4.1763 | 0.7240 |
| 4.4331 | 20.2335 | 480000 | 4.1728 | 0.7246 |
| 4.4282 | 20.6551 | 490000 | 4.1693 | 0.7250 |
| 4.4242 | 21.0766 | 500000 | 4.1657 | 0.7254 |
| 4.4206 | 21.4981 | 510000 | 4.1630 | 0.7259 |
| 4.4165 | 21.9197 | 520000 | 4.1615 | 0.7262 |
| 4.4196 | 22.3412 | 530000 | 4.1590 | 0.7266 |
| 4.412 | 22.7627 | 540000 | 4.1587 | 0.7267 |
| 4.4122 | 23.1843 | 550000 | 4.1542 | 0.7271 |
| 4.4097 | 23.6058 | 560000 | 4.1519 | 0.7277 |
| 4.4042 | 24.0273 | 570000 | 4.1513 | 0.7278 |
| 4.4037 | 24.4488 | 580000 | 4.1470 | 0.7284 |
| 4.401 | 24.8704 | 590000 | 4.1480 | 0.7281 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3