| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: spell_correction_M02_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_M02_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: 0.0138 |
| | |
| | ## 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 | 263 | 0.3208 | |
| | | 1.8633 | 2.0 | 526 | 0.0425 | |
| | | 1.8633 | 3.0 | 789 | 0.0253 | |
| | | 0.037 | 4.0 | 1052 | 0.0210 | |
| | | 0.037 | 5.0 | 1315 | 0.0172 | |
| | | 0.015 | 6.0 | 1578 | 0.0162 | |
| | | 0.015 | 7.0 | 1841 | 0.0156 | |
| | | 0.01 | 8.0 | 2104 | 0.0151 | |
| | | 0.01 | 9.0 | 2367 | 0.0150 | |
| | | 0.0063 | 10.0 | 2630 | 0.0153 | |
| | | 0.0063 | 11.0 | 2893 | 0.0141 | |
| | | 0.0049 | 12.0 | 3156 | 0.0140 | |
| | | 0.0049 | 13.0 | 3419 | 0.0150 | |
| | | 0.0039 | 14.0 | 3682 | 0.0136 | |
| | | 0.0039 | 15.0 | 3945 | 0.0147 | |
| | | 0.0027 | 16.0 | 4208 | 0.0142 | |
| | | 0.0027 | 17.0 | 4471 | 0.0128 | |
| | | 0.0028 | 18.0 | 4734 | 0.0128 | |
| | | 0.0028 | 19.0 | 4997 | 0.0128 | |
| | | 0.0029 | 20.0 | 5260 | 0.0131 | |
| | | 0.0022 | 21.0 | 5523 | 0.0139 | |
| | | 0.0022 | 22.0 | 5786 | 0.0144 | |
| | | 0.0018 | 23.0 | 6049 | 0.0136 | |
| | | 0.0018 | 24.0 | 6312 | 0.0134 | |
| | | 0.002 | 25.0 | 6575 | 0.0143 | |
| | | 0.002 | 26.0 | 6838 | 0.0137 | |
| | | 0.0016 | 27.0 | 7101 | 0.0137 | |
| | | 0.0016 | 28.0 | 7364 | 0.0140 | |
| | | 0.0018 | 29.0 | 7627 | 0.0139 | |
| | | 0.0018 | 30.0 | 7890 | 0.0138 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.28.0 |
| | - Pytorch 1.12.1+cu102 |
| | - Datasets 2.13.1 |
| | - Tokenizers 0.13.3 |
| | |
