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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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datasets: |
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- gokulsrinivasagan/processed_book_corpus-ld-5 |
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metrics: |
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- accuracy |
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model-index: |
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- name: bert_base_lda_5_v1_book |
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results: |
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- task: |
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name: Masked Language Modeling |
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type: fill-mask |
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dataset: |
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name: gokulsrinivasagan/processed_book_corpus-ld-5 |
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type: gokulsrinivasagan/processed_book_corpus-ld-5 |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.7558573418429354 |
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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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# bert_base_lda_5_v1_book |
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This model is a fine-tuned version of [](https://huggingface.co/) on the gokulsrinivasagan/processed_book_corpus-ld-5 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.4588 |
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- Accuracy: 0.7559 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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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 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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-------:|:------:|:---------------:|:--------:| |
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| 7.0997 | 0.4215 | 10000 | 6.9318 | 0.1639 | |
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| 6.9855 | 0.8431 | 20000 | 6.8420 | 0.1652 | |
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| 6.9276 | 1.2646 | 30000 | 6.7965 | 0.1662 | |
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| 6.8979 | 1.6861 | 40000 | 6.7707 | 0.1664 | |
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| 6.8708 | 2.1077 | 50000 | 6.7510 | 0.1673 | |
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| 6.8545 | 2.5292 | 60000 | 6.7322 | 0.1682 | |
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| 4.1528 | 2.9507 | 70000 | 3.8084 | 0.5410 | |
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| 3.5714 | 3.3723 | 80000 | 3.2838 | 0.6196 | |
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| 3.3831 | 3.7938 | 90000 | 3.1109 | 0.6470 | |
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| 3.2724 | 4.2153 | 100000 | 3.0118 | 0.6628 | |
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| 3.2036 | 4.6369 | 110000 | 2.9437 | 0.6732 | |
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| 3.1442 | 5.0584 | 120000 | 2.8917 | 0.6821 | |
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| 3.0973 | 5.4799 | 130000 | 2.8480 | 0.6892 | |
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| 3.0658 | 5.9014 | 140000 | 2.8130 | 0.6946 | |
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| 3.03 | 6.3230 | 150000 | 2.7858 | 0.6993 | |
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| 3.0096 | 6.7445 | 160000 | 2.7617 | 0.7035 | |
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| 2.9758 | 7.1660 | 170000 | 2.7381 | 0.7077 | |
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| 2.9593 | 7.5876 | 180000 | 2.7242 | 0.7101 | |
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| 2.9411 | 8.0091 | 190000 | 2.7034 | 0.7130 | |
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| 2.923 | 8.4306 | 200000 | 2.6897 | 0.7158 | |
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| 2.9048 | 8.8522 | 210000 | 2.6765 | 0.7181 | |
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| 2.8966 | 9.2737 | 220000 | 2.6622 | 0.7204 | |
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| 2.8762 | 9.6952 | 230000 | 2.6505 | 0.7223 | |
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| 2.8607 | 10.1168 | 240000 | 2.6398 | 0.7245 | |
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| 2.8571 | 10.5383 | 250000 | 2.6271 | 0.7262 | |
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| 2.8425 | 10.9598 | 260000 | 2.6175 | 0.7280 | |
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| 2.8318 | 11.3814 | 270000 | 2.6108 | 0.7292 | |
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| 2.8289 | 11.8029 | 280000 | 2.6007 | 0.7311 | |
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| 2.8124 | 12.2244 | 290000 | 2.5929 | 0.7324 | |
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| 2.8057 | 12.6460 | 300000 | 2.5821 | 0.7343 | |
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| 2.7945 | 13.0675 | 310000 | 2.5765 | 0.7354 | |
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| 2.7875 | 13.4890 | 320000 | 2.5697 | 0.7366 | |
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| 2.782 | 13.9106 | 330000 | 2.5634 | 0.7373 | |
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| 2.7765 | 14.3321 | 340000 | 2.5552 | 0.7390 | |
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| 2.7667 | 14.7536 | 350000 | 2.5493 | 0.7398 | |
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| 2.7611 | 15.1751 | 360000 | 2.5438 | 0.7407 | |
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| 2.7551 | 15.5967 | 370000 | 2.5371 | 0.7419 | |
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| 2.7481 | 16.0182 | 380000 | 2.5313 | 0.7430 | |
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| 2.7426 | 16.4397 | 390000 | 2.5264 | 0.7439 | |
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| 2.7361 | 16.8613 | 400000 | 2.5229 | 0.7447 | |
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| 2.7309 | 17.2828 | 410000 | 2.5152 | 0.7458 | |
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| 2.7245 | 17.7043 | 420000 | 2.5121 | 0.7467 | |
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| 2.7188 | 18.1259 | 430000 | 2.5086 | 0.7471 | |
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| 2.7113 | 18.5474 | 440000 | 2.5051 | 0.7478 | |
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| 2.7108 | 18.9689 | 450000 | 2.4989 | 0.7489 | |
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| 2.7047 | 19.3905 | 460000 | 2.4949 | 0.7496 | |
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| 2.7021 | 19.8120 | 470000 | 2.4909 | 0.7502 | |
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| 2.6941 | 20.2335 | 480000 | 2.4869 | 0.7509 | |
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| 2.6883 | 20.6551 | 490000 | 2.4828 | 0.7516 | |
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| 2.6843 | 21.0766 | 500000 | 2.4785 | 0.7522 | |
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| 2.681 | 21.4981 | 510000 | 2.4755 | 0.7530 | |
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| 2.6756 | 21.9197 | 520000 | 2.4729 | 0.7535 | |
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| 2.6757 | 22.3412 | 530000 | 2.4707 | 0.7539 | |
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| 2.6705 | 22.7627 | 540000 | 2.4694 | 0.7541 | |
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| 2.6708 | 23.1843 | 550000 | 2.4654 | 0.7545 | |
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| 2.6665 | 23.6058 | 560000 | 2.4626 | 0.7553 | |
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| 2.6622 | 24.0273 | 570000 | 2.4618 | 0.7555 | |
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| 2.6612 | 24.4488 | 580000 | 2.4580 | 0.7561 | |
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| 2.6573 | 24.8704 | 590000 | 2.4581 | 0.7559 | |
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### Framework versions |
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- Transformers 4.46.3 |
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- Pytorch 2.2.1+cu118 |
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- Datasets 2.17.0 |
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- Tokenizers 0.20.3 |
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