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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_tiny_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: 0.6765868602733887 |
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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_tiny_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: 4.9524 |
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- Accuracy: 0.6766 |
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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: 160 |
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- eval_batch_size: 160 |
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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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-------:|:------:|:---------------:|:--------:| |
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| 10.2267 | 0.7025 | 10000 | 10.0665 | 0.1636 | |
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| 7.2173 | 1.4051 | 20000 | 6.7451 | 0.4823 | |
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| 6.4475 | 2.1076 | 30000 | 6.0308 | 0.5509 | |
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| 6.1492 | 2.8102 | 40000 | 5.7522 | 0.5804 | |
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| 5.9566 | 3.5127 | 50000 | 5.5702 | 0.6009 | |
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| 5.8259 | 4.2153 | 60000 | 5.4546 | 0.6137 | |
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| 5.7396 | 4.9178 | 70000 | 5.3672 | 0.6239 | |
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| 5.6664 | 5.6203 | 80000 | 5.3074 | 0.6312 | |
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| 5.6155 | 6.3229 | 90000 | 5.2622 | 0.6366 | |
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| 5.5704 | 7.0254 | 100000 | 5.2177 | 0.6416 | |
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| 5.5381 | 7.7280 | 110000 | 5.1869 | 0.6460 | |
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| 5.5072 | 8.4305 | 120000 | 5.1572 | 0.6495 | |
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| 5.476 | 9.1331 | 130000 | 5.1399 | 0.6520 | |
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| 5.4586 | 9.8356 | 140000 | 5.1144 | 0.6554 | |
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| 5.4395 | 10.5381 | 150000 | 5.0980 | 0.6573 | |
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| 5.4279 | 11.2407 | 160000 | 5.0854 | 0.6588 | |
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| 5.4084 | 11.9432 | 170000 | 5.0694 | 0.6610 | |
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| 5.3943 | 12.6458 | 180000 | 5.0544 | 0.6627 | |
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| 5.3829 | 13.3483 | 190000 | 5.0477 | 0.6636 | |
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| 5.374 | 14.0509 | 200000 | 5.0361 | 0.6652 | |
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| 5.3602 | 14.7534 | 210000 | 5.0257 | 0.6666 | |
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| 5.3506 | 15.4560 | 220000 | 5.0155 | 0.6681 | |
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| 5.3443 | 16.1585 | 230000 | 5.0103 | 0.6687 | |
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| 5.3334 | 16.8610 | 240000 | 5.0030 | 0.6697 | |
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| 5.3252 | 17.5636 | 250000 | 4.9964 | 0.6705 | |
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| 5.3187 | 18.2661 | 260000 | 4.9904 | 0.6711 | |
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| 5.3167 | 18.9687 | 270000 | 4.9849 | 0.6723 | |
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| 5.3068 | 19.6712 | 280000 | 4.9791 | 0.6731 | |
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| 5.3031 | 20.3738 | 290000 | 4.9740 | 0.6736 | |
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| 5.2947 | 21.0763 | 300000 | 4.9701 | 0.6742 | |
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| 5.2931 | 21.7788 | 310000 | 4.9633 | 0.6752 | |
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| 5.2875 | 22.4814 | 320000 | 4.9602 | 0.6756 | |
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| 5.2841 | 23.1839 | 330000 | 4.9582 | 0.6758 | |
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| 5.2815 | 23.8865 | 340000 | 4.9541 | 0.6762 | |
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| 5.2811 | 24.5890 | 350000 | 4.9512 | 0.6766 | |
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### Framework versions |
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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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