| --- |
| license: apache-2.0 |
| base_model: google/mt5-small |
| tags: |
| - generated_from_trainer |
| metrics: |
| - bleu |
| model-index: |
| - name: spell_corrector_small_v7 |
| 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_corrector_small_v7 |
| |
| This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.5549 |
| - Bleu: 34.7876 |
| - Gen Len: 15.7815 |
| |
| ## 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: 2e-05 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 20 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len | |
| |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:| |
| | 14.2184 | 1.0 | 976 | 1.6501 | 16.2132 | 13.5571 | |
| | 2.8018 | 2.0 | 1952 | 1.2055 | 23.1195 | 15.9748 | |
| | 2.0238 | 3.0 | 2928 | 0.9646 | 26.7454 | 15.9865 | |
| | 1.6928 | 4.0 | 3904 | 0.8372 | 28.6482 | 15.9601 | |
| | 1.4888 | 5.0 | 4880 | 0.7906 | 29.6306 | 15.9221 | |
| | 1.3855 | 6.0 | 5856 | 0.7393 | 30.3841 | 15.9006 | |
| | 1.2999 | 7.0 | 6832 | 0.7029 | 31.2225 | 15.8612 | |
| | 1.2379 | 8.0 | 7808 | 0.6794 | 31.6015 | 15.8666 | |
| | 1.1709 | 9.0 | 8784 | 0.6572 | 32.2153 | 15.8512 | |
| | 1.1433 | 10.0 | 9760 | 0.6303 | 32.7529 | 15.8288 | |
| | 1.1248 | 11.0 | 10736 | 0.6184 | 33.144 | 15.8244 | |
| | 1.0703 | 12.0 | 11712 | 0.6072 | 33.4743 | 15.8121 | |
| | 1.0547 | 13.0 | 12688 | 0.5937 | 33.7492 | 15.8139 | |
| | 1.0275 | 14.0 | 13664 | 0.5779 | 34.1454 | 15.7952 | |
| | 1.0122 | 15.0 | 14640 | 0.5727 | 34.2908 | 15.7907 | |
| | 1.0071 | 16.0 | 15616 | 0.5662 | 34.4457 | 15.7874 | |
| | 1.0017 | 17.0 | 16592 | 0.5609 | 34.6225 | 15.7847 | |
| | 0.9879 | 18.0 | 17568 | 0.5575 | 34.6937 | 15.7832 | |
| | 0.9814 | 19.0 | 18544 | 0.5554 | 34.7827 | 15.7816 | |
| | 0.9793 | 20.0 | 19520 | 0.5549 | 34.7876 | 15.7815 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.31.0 |
| - Pytorch 2.0.1+cu118 |
| - Datasets 2.14.2 |
| - Tokenizers 0.13.3 |
| |
