| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: spell_correction_F01_LM |
| | results: [] |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # spell_correction_F01_LM |
| | |
| | This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.0147 |
| | |
| | ## 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: 1e-05 |
| | - train_batch_size: 16 |
| | - eval_batch_size: 16 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 30 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | |
| | |:-------------:|:-----:|:----:|:---------------:| |
| | | No log | 1.0 | 294 | 0.1889 | |
| | | 1.8488 | 2.0 | 588 | 0.0392 | |
| | | 1.8488 | 3.0 | 882 | 0.0260 | |
| | | 0.0369 | 4.0 | 1176 | 0.0212 | |
| | | 0.0369 | 5.0 | 1470 | 0.0170 | |
| | | 0.0182 | 6.0 | 1764 | 0.0162 | |
| | | 0.0105 | 7.0 | 2058 | 0.0173 | |
| | | 0.0105 | 8.0 | 2352 | 0.0177 | |
| | | 0.0083 | 9.0 | 2646 | 0.0176 | |
| | | 0.0083 | 10.0 | 2940 | 0.0164 | |
| | | 0.0057 | 11.0 | 3234 | 0.0149 | |
| | | 0.0037 | 12.0 | 3528 | 0.0168 | |
| | | 0.0037 | 13.0 | 3822 | 0.0164 | |
| | | 0.003 | 14.0 | 4116 | 0.0156 | |
| | | 0.003 | 15.0 | 4410 | 0.0151 | |
| | | 0.003 | 16.0 | 4704 | 0.0152 | |
| | | 0.003 | 17.0 | 4998 | 0.0149 | |
| | | 0.0028 | 18.0 | 5292 | 0.0153 | |
| | | 0.002 | 19.0 | 5586 | 0.0146 | |
| | | 0.002 | 20.0 | 5880 | 0.0147 | |
| | | 0.0021 | 21.0 | 6174 | 0.0146 | |
| | | 0.0021 | 22.0 | 6468 | 0.0149 | |
| | | 0.0025 | 23.0 | 6762 | 0.0146 | |
| | | 0.0018 | 24.0 | 7056 | 0.0150 | |
| | | 0.0018 | 25.0 | 7350 | 0.0147 | |
| | | 0.0021 | 26.0 | 7644 | 0.0145 | |
| | | 0.0021 | 27.0 | 7938 | 0.0147 | |
| | | 0.0017 | 28.0 | 8232 | 0.0146 | |
| | | 0.0014 | 29.0 | 8526 | 0.0147 | |
| | | 0.0014 | 30.0 | 8820 | 0.0147 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.28.0 |
| | - Pytorch 1.12.1+cu102 |
| | - Datasets 2.13.1 |
| | - Tokenizers 0.13.3 |
| | |
