| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: spell_correction_M04_V3 |
| | 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_M04_V3 |
| | |
| | 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: 0.0178 |
| | |
| | ## 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 | 269 | 0.2687 | |
| | | 1.8467 | 2.0 | 538 | 0.0361 | |
| | | 1.8467 | 3.0 | 807 | 0.0241 | |
| | | 0.0357 | 4.0 | 1076 | 0.0198 | |
| | | 0.0357 | 5.0 | 1345 | 0.0199 | |
| | | 0.0159 | 6.0 | 1614 | 0.0175 | |
| | | 0.0159 | 7.0 | 1883 | 0.0179 | |
| | | 0.0077 | 8.0 | 2152 | 0.0189 | |
| | | 0.0077 | 9.0 | 2421 | 0.0183 | |
| | | 0.006 | 10.0 | 2690 | 0.0183 | |
| | | 0.006 | 11.0 | 2959 | 0.0191 | |
| | | 0.0044 | 12.0 | 3228 | 0.0186 | |
| | | 0.0044 | 13.0 | 3497 | 0.0192 | |
| | | 0.0033 | 14.0 | 3766 | 0.0189 | |
| | | 0.0024 | 15.0 | 4035 | 0.0173 | |
| | | 0.0024 | 16.0 | 4304 | 0.0171 | |
| | | 0.0026 | 17.0 | 4573 | 0.0183 | |
| | | 0.0026 | 18.0 | 4842 | 0.0181 | |
| | | 0.0021 | 19.0 | 5111 | 0.0177 | |
| | | 0.0021 | 20.0 | 5380 | 0.0174 | |
| | | 0.0015 | 21.0 | 5649 | 0.0173 | |
| | | 0.0015 | 22.0 | 5918 | 0.0174 | |
| | | 0.0016 | 23.0 | 6187 | 0.0178 | |
| | | 0.0016 | 24.0 | 6456 | 0.0180 | |
| | | 0.0018 | 25.0 | 6725 | 0.0175 | |
| | | 0.0018 | 26.0 | 6994 | 0.0171 | |
| | | 0.0017 | 27.0 | 7263 | 0.0175 | |
| | | 0.0014 | 28.0 | 7532 | 0.0177 | |
| | | 0.0014 | 29.0 | 7801 | 0.0178 | |
| | | 0.0013 | 30.0 | 8070 | 0.0178 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.28.0 |
| | - Pytorch 1.12.1+cu102 |
| | - Datasets 2.13.1 |
| | - Tokenizers 0.13.3 |
| | |
