| | --- |
| | library_name: transformers |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - gokulsrinivasagan/processed_book_corpus-ld |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: bert_tiny_lda_book |
| | results: |
| | - task: |
| | name: Masked Language Modeling |
| | type: fill-mask |
| | dataset: |
| | name: gokulsrinivasagan/processed_book_corpus-ld |
| | type: gokulsrinivasagan/processed_book_corpus-ld |
| | metrics: |
| | - name: Accuracy |
| | type: accuracy |
| | value: 0.6827213137673483 |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # bert_tiny_lda_book |
| | |
| | This model is a fine-tuned version of [](https://huggingface.co/) on the gokulsrinivasagan/processed_book_corpus-ld dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 3.3915 |
| | - Accuracy: 0.6827 |
| | |
| | ## 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: 160 |
| | - eval_batch_size: 160 |
| | - seed: 10 |
| | - optimizer: Use OptimizerNames.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 | |
| | |:-------------:|:-------:|:------:|:---------------:|:--------:| |
| | | 7.9444 | 0.7025 | 10000 | 7.7823 | 0.1644 | |
| | | 5.4537 | 1.4051 | 20000 | 5.0087 | 0.4658 | |
| | | 4.6397 | 2.1076 | 30000 | 4.2650 | 0.5607 | |
| | | 4.3898 | 2.8102 | 40000 | 4.0379 | 0.5916 | |
| | | 4.2383 | 3.5127 | 50000 | 3.8978 | 0.6113 | |
| | | 4.1379 | 4.2153 | 60000 | 3.8117 | 0.6234 | |
| | | 4.0736 | 4.9178 | 70000 | 3.7462 | 0.6324 | |
| | | 4.0187 | 5.6203 | 80000 | 3.6985 | 0.6391 | |
| | | 3.9803 | 6.3229 | 90000 | 3.6644 | 0.6444 | |
| | | 3.9462 | 7.0254 | 100000 | 3.6333 | 0.6485 | |
| | | 3.9217 | 7.7280 | 110000 | 3.6064 | 0.6526 | |
| | | 3.8974 | 8.4305 | 120000 | 3.5810 | 0.6558 | |
| | | 3.8714 | 9.1331 | 130000 | 3.5696 | 0.6581 | |
| | | 3.8565 | 9.8356 | 140000 | 3.5454 | 0.6613 | |
| | | 3.8382 | 10.5381 | 150000 | 3.5310 | 0.6632 | |
| | | 3.8272 | 11.2407 | 160000 | 3.5181 | 0.6647 | |
| | | 3.8059 | 11.9432 | 170000 | 3.5012 | 0.6666 | |
| | | 3.7935 | 12.6458 | 180000 | 3.4849 | 0.6683 | |
| | | 3.7815 | 13.3483 | 190000 | 3.4784 | 0.6695 | |
| | | 3.7719 | 14.0509 | 200000 | 3.4671 | 0.6710 | |
| | | 3.7614 | 14.7534 | 210000 | 3.4574 | 0.6724 | |
| | | 3.7509 | 15.4560 | 220000 | 3.4488 | 0.6740 | |
| | | 3.7456 | 16.1585 | 230000 | 3.4445 | 0.6745 | |
| | | 3.736 | 16.8610 | 240000 | 3.4378 | 0.6753 | |
| | | 3.728 | 17.5636 | 250000 | 3.4330 | 0.6763 | |
| | | 3.7223 | 18.2661 | 260000 | 3.4270 | 0.6772 | |
| | | 3.7195 | 18.9687 | 270000 | 3.4210 | 0.6780 | |
| | | 3.7104 | 19.6712 | 280000 | 3.4156 | 0.6790 | |
| | | 3.7086 | 20.3738 | 290000 | 3.4105 | 0.6797 | |
| | | 3.7002 | 21.0763 | 300000 | 3.4070 | 0.6803 | |
| | | 3.698 | 21.7788 | 310000 | 3.4013 | 0.6812 | |
| | | 3.6915 | 22.4814 | 320000 | 3.3987 | 0.6814 | |
| | | 3.6909 | 23.1839 | 330000 | 3.3962 | 0.6818 | |
| | | 3.6883 | 23.8865 | 340000 | 3.3933 | 0.6825 | |
| | | 3.6867 | 24.5890 | 350000 | 3.3903 | 0.6829 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.46.1 |
| | - Pytorch 2.2.0+cu121 |
| | - Datasets 3.1.0 |
| | - Tokenizers 0.20.1 |
| |
|
