| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: spell_correction_F03_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_F03_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: 0.0490 |
| | |
| | ## 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 | 248 | 1.0015 | |
| | | No log | 2.0 | 496 | 0.3499 | |
| | | 2.4465 | 3.0 | 744 | 0.1456 | |
| | | 2.4465 | 4.0 | 992 | 0.0854 | |
| | | 0.1986 | 5.0 | 1240 | 0.0689 | |
| | | 0.1986 | 6.0 | 1488 | 0.0619 | |
| | | 0.0578 | 7.0 | 1736 | 0.0571 | |
| | | 0.0578 | 8.0 | 1984 | 0.0525 | |
| | | 0.0269 | 9.0 | 2232 | 0.0524 | |
| | | 0.0269 | 10.0 | 2480 | 0.0517 | |
| | | 0.0172 | 11.0 | 2728 | 0.0498 | |
| | | 0.0172 | 12.0 | 2976 | 0.0488 | |
| | | 0.0113 | 13.0 | 3224 | 0.0500 | |
| | | 0.0113 | 14.0 | 3472 | 0.0493 | |
| | | 0.0088 | 15.0 | 3720 | 0.0496 | |
| | | 0.0088 | 16.0 | 3968 | 0.0495 | |
| | | 0.0077 | 17.0 | 4216 | 0.0477 | |
| | | 0.0077 | 18.0 | 4464 | 0.0489 | |
| | | 0.0066 | 19.0 | 4712 | 0.0476 | |
| | | 0.0066 | 20.0 | 4960 | 0.0489 | |
| | | 0.0064 | 21.0 | 5208 | 0.0486 | |
| | | 0.0064 | 22.0 | 5456 | 0.0494 | |
| | | 0.0063 | 23.0 | 5704 | 0.0494 | |
| | | 0.0063 | 24.0 | 5952 | 0.0497 | |
| | | 0.004 | 25.0 | 6200 | 0.0495 | |
| | | 0.004 | 26.0 | 6448 | 0.0493 | |
| | | 0.0045 | 27.0 | 6696 | 0.0491 | |
| | | 0.0045 | 28.0 | 6944 | 0.0490 | |
| | | 0.0039 | 29.0 | 7192 | 0.0490 | |
| | | 0.0039 | 30.0 | 7440 | 0.0490 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.28.0 |
| | - Pytorch 1.12.1+cu102 |
| | - Datasets 2.13.1 |
| | - Tokenizers 0.13.3 |
| | |
