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gokulsrinivasagan
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bert_base_lda_book

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distilbert
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  2. logs/events.out.tfevents.1733401021.ki-g0009.1443937.0 +2 -2
README.md ADDED
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+ ---
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+ library_name: transformers
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: bert_base_lda_book
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # bert_base_lda_book
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+
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+ This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 2.9464
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+ - Accuracy: 0.7610
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.0001
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+ - train_batch_size: 96
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+ - eval_batch_size: 96
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+ - seed: 10
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 10000
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+ - num_epochs: 25
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-------:|:------:|:---------------:|:--------:|
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+ | 7.6611 | 0.4215 | 10000 | 7.4831 | 0.1626 |
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+ | 7.54 | 0.8431 | 20000 | 7.3893 | 0.1640 |
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+ | 7.477 | 1.2646 | 30000 | 7.3399 | 0.1663 |
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+ | 7.4478 | 1.6861 | 40000 | 7.3119 | 0.1667 |
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+ | 5.084 | 2.1077 | 50000 | 4.6037 | 0.4982 |
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+ | 4.1458 | 2.5292 | 60000 | 3.8418 | 0.6153 |
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+ | 3.9219 | 2.9507 | 70000 | 3.6449 | 0.6468 |
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+ | 3.8057 | 3.3723 | 80000 | 3.5337 | 0.6641 |
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+ | 3.7243 | 3.7938 | 90000 | 3.4573 | 0.6761 |
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+ | 3.6613 | 4.2153 | 100000 | 3.4046 | 0.6845 |
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+ | 3.6198 | 4.6369 | 110000 | 3.3638 | 0.6910 |
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+ | 3.5769 | 5.0584 | 120000 | 3.3235 | 0.6972 |
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+ | 3.5446 | 5.4799 | 130000 | 3.2929 | 0.7021 |
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+ | 3.5226 | 5.9014 | 140000 | 3.2670 | 0.7062 |
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+ | 3.493 | 6.3230 | 150000 | 3.2465 | 0.7099 |
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+ | 3.4784 | 6.7445 | 160000 | 3.2292 | 0.7130 |
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+ | 3.4465 | 7.1660 | 170000 | 3.2074 | 0.7165 |
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+ | 3.433 | 7.5876 | 180000 | 3.1960 | 0.7186 |
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+ | 3.4171 | 8.0091 | 190000 | 3.1785 | 0.7212 |
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+ | 3.4016 | 8.4306 | 200000 | 3.1640 | 0.7237 |
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+ | 3.3853 | 8.8522 | 210000 | 3.1538 | 0.7257 |
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+ | 3.3776 | 9.2737 | 220000 | 3.1404 | 0.7278 |
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+ | 3.3568 | 9.6952 | 230000 | 3.1291 | 0.7295 |
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+ | 3.3441 | 10.1168 | 240000 | 3.1205 | 0.7315 |
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+ | 3.341 | 10.5383 | 250000 | 3.1095 | 0.7328 |
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+ | 3.3292 | 10.9598 | 260000 | 3.1005 | 0.7345 |
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+ | 3.3173 | 11.3814 | 270000 | 3.0944 | 0.7355 |
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+ | 3.3162 | 11.8029 | 280000 | 3.0838 | 0.7373 |
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+ | 3.298 | 12.2244 | 290000 | 3.0764 | 0.7386 |
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+ | 3.293 | 12.6460 | 300000 | 3.0676 | 0.7400 |
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+ | 3.2808 | 13.0675 | 310000 | 3.0613 | 0.7413 |
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+ | 3.2786 | 13.4890 | 320000 | 3.0542 | 0.7423 |
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+ | 3.2717 | 13.9106 | 330000 | 3.0505 | 0.7432 |
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+ | 3.266 | 14.3321 | 340000 | 3.0427 | 0.7445 |
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+ | 3.2583 | 14.7536 | 350000 | 3.0360 | 0.7454 |
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+ | 3.2508 | 15.1751 | 360000 | 3.0327 | 0.7461 |
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+ | 3.2454 | 15.5967 | 370000 | 3.0232 | 0.7474 |
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+ | 3.2386 | 16.0182 | 380000 | 3.0186 | 0.7484 |
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+ | 3.2334 | 16.4397 | 390000 | 3.0147 | 0.7492 |
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+ | 3.2251 | 16.8613 | 400000 | 3.0106 | 0.7499 |
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+ | 3.2228 | 17.2828 | 410000 | 3.0035 | 0.7511 |
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+ | 3.2162 | 17.7043 | 420000 | 3.0003 | 0.7517 |
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+ | 3.2079 | 18.1259 | 430000 | 2.9971 | 0.7524 |
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+ | 3.2024 | 18.5474 | 440000 | 2.9928 | 0.7530 |
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+ | 3.2014 | 18.9689 | 450000 | 2.9856 | 0.7541 |
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+ | 3.1962 | 19.3905 | 460000 | 2.9826 | 0.7547 |
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+ | 3.1917 | 19.8120 | 470000 | 2.9786 | 0.7555 |
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+ | 3.1854 | 20.2335 | 480000 | 2.9755 | 0.7561 |
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+ | 3.18 | 20.6551 | 490000 | 2.9711 | 0.7567 |
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+ | 3.1744 | 21.0766 | 500000 | 2.9676 | 0.7573 |
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+ | 3.1714 | 21.4981 | 510000 | 2.9635 | 0.7580 |
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+ | 3.1664 | 21.9197 | 520000 | 2.9616 | 0.7583 |
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+ | 3.1674 | 22.3412 | 530000 | 2.9592 | 0.7588 |
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+ | 3.1614 | 22.7627 | 540000 | 2.9579 | 0.7591 |
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+ | 3.1616 | 23.1843 | 550000 | 2.9536 | 0.7597 |
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+ | 3.1579 | 23.6058 | 560000 | 2.9513 | 0.7603 |
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+ | 3.154 | 24.0273 | 570000 | 2.9501 | 0.7605 |
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+ | 3.1504 | 24.4488 | 580000 | 2.9464 | 0.7610 |
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+ | 3.1482 | 24.8704 | 590000 | 2.9464 | 0.7610 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.46.1
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+ - Pytorch 2.2.0+cu121
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+ - Datasets 3.1.0
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+ - Tokenizers 0.20.1
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