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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-100 |
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metrics: |
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- accuracy |
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model-index: |
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- name: bert_base_lda_100_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-100 |
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type: gokulsrinivasagan/processed_book_corpus-ld-100 |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.7551218228545009 |
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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_100_v1_book |
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This model is a fine-tuned version of [](https://huggingface.co/) on the gokulsrinivasagan/processed_book_corpus-ld-100 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 4.4757 |
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- Accuracy: 0.7551 |
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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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| 9.5861 | 0.4215 | 10000 | 9.3593 | 0.1636 | |
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| 9.2311 | 0.8431 | 20000 | 9.0701 | 0.1641 | |
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| 9.1362 | 1.2646 | 30000 | 8.9889 | 0.1662 | |
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| 6.984 | 1.6861 | 40000 | 6.4486 | 0.4683 | |
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| 5.8878 | 2.1077 | 50000 | 5.5436 | 0.5941 | |
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| 5.6092 | 2.5292 | 60000 | 5.2862 | 0.6336 | |
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| 5.4567 | 2.9507 | 70000 | 5.1556 | 0.6531 | |
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| 5.3612 | 3.3723 | 80000 | 5.0665 | 0.6665 | |
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| 5.2881 | 3.7938 | 90000 | 4.9997 | 0.6763 | |
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| 5.2269 | 4.2153 | 100000 | 4.9488 | 0.6834 | |
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| 5.1854 | 4.6369 | 110000 | 4.9087 | 0.6889 | |
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| 5.1474 | 5.0584 | 120000 | 4.8727 | 0.6944 | |
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| 5.1144 | 5.4799 | 130000 | 4.8404 | 0.6990 | |
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| 5.0914 | 5.9014 | 140000 | 4.8134 | 0.7026 | |
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| 5.0579 | 6.3230 | 150000 | 4.7935 | 0.7058 | |
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| 5.044 | 6.7445 | 160000 | 4.7736 | 0.7089 | |
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| 5.0124 | 7.1660 | 170000 | 4.7533 | 0.7124 | |
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| 4.9997 | 7.5876 | 180000 | 4.7431 | 0.7140 | |
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| 4.9809 | 8.0091 | 190000 | 4.7224 | 0.7163 | |
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| 4.9674 | 8.4306 | 200000 | 4.7087 | 0.7189 | |
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| 4.9526 | 8.8522 | 210000 | 4.6976 | 0.7206 | |
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| 4.9422 | 9.2737 | 220000 | 4.6848 | 0.7224 | |
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| 4.9232 | 9.6952 | 230000 | 4.6721 | 0.7242 | |
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| 4.9073 | 10.1168 | 240000 | 4.6646 | 0.7261 | |
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| 4.9072 | 10.5383 | 250000 | 4.6502 | 0.7276 | |
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| 4.8916 | 10.9598 | 260000 | 4.6415 | 0.7290 | |
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| 4.8805 | 11.3814 | 270000 | 4.6341 | 0.7301 | |
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| 4.8775 | 11.8029 | 280000 | 4.6231 | 0.7318 | |
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| 4.86 | 12.2244 | 290000 | 4.6168 | 0.7330 | |
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| 4.8539 | 12.6460 | 300000 | 4.6066 | 0.7346 | |
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| 4.8416 | 13.0675 | 310000 | 4.5990 | 0.7359 | |
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| 4.8371 | 13.4890 | 320000 | 4.5932 | 0.7366 | |
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| 4.8312 | 13.9106 | 330000 | 4.5877 | 0.7373 | |
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| 4.8264 | 14.3321 | 340000 | 4.5786 | 0.7392 | |
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| 4.8157 | 14.7536 | 350000 | 4.5722 | 0.7398 | |
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| 4.8097 | 15.1751 | 360000 | 4.5686 | 0.7404 | |
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| 4.8045 | 15.5967 | 370000 | 4.5596 | 0.7416 | |
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| 4.7951 | 16.0182 | 380000 | 4.5546 | 0.7427 | |
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| 4.7906 | 16.4397 | 390000 | 4.5487 | 0.7434 | |
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| 4.7858 | 16.8613 | 400000 | 4.5452 | 0.7441 | |
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| 4.7798 | 17.2828 | 410000 | 4.5381 | 0.7452 | |
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| 4.7725 | 17.7043 | 420000 | 4.5330 | 0.7461 | |
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| 4.7628 | 18.1259 | 430000 | 4.5300 | 0.7466 | |
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| 4.7584 | 18.5474 | 440000 | 4.5251 | 0.7472 | |
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| 4.7573 | 18.9689 | 450000 | 4.5193 | 0.7483 | |
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| 4.7502 | 19.3905 | 460000 | 4.5154 | 0.7488 | |
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| 4.7482 | 19.8120 | 470000 | 4.5109 | 0.7496 | |
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| 4.738 | 20.2335 | 480000 | 4.5065 | 0.7502 | |
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| 4.7328 | 20.6551 | 490000 | 4.5021 | 0.7509 | |
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| 4.7289 | 21.0766 | 500000 | 4.4975 | 0.7515 | |
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| 4.7235 | 21.4981 | 510000 | 4.4950 | 0.7521 | |
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| 4.7191 | 21.9197 | 520000 | 4.4923 | 0.7525 | |
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| 4.7191 | 22.3412 | 530000 | 4.4891 | 0.7530 | |
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| 4.714 | 22.7627 | 540000 | 4.4877 | 0.7534 | |
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| 4.714 | 23.1843 | 550000 | 4.4832 | 0.7539 | |
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| 4.7086 | 23.6058 | 560000 | 4.4800 | 0.7544 | |
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| 4.7055 | 24.0273 | 570000 | 4.4785 | 0.7547 | |
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| 4.7024 | 24.4488 | 580000 | 4.4747 | 0.7552 | |
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| 4.6993 | 24.8704 | 590000 | 4.4753 | 0.7550 | |
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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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