| --- |
| tags: |
| - generated_from_trainer |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: transliterate |
| 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. --> |
|
|
| # transliterate |
|
|
| This model was trained from scratch on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0324 |
| - Precision: 0.9912 |
| - Recall: 0.9912 |
| - F1: 0.9912 |
| - Accuracy: 0.9912 |
|
|
| ## 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: 32 |
| - eval_batch_size: 32 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 10 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | No log | 1.0 | 64 | 0.1049 | 0.9654 | 0.9654 | 0.9654 | 0.9654 | |
| | No log | 2.0 | 128 | 0.0665 | 0.9796 | 0.9796 | 0.9796 | 0.9796 | |
| | No log | 3.0 | 192 | 0.0513 | 0.9848 | 0.9848 | 0.9848 | 0.9848 | |
| | No log | 4.0 | 256 | 0.0434 | 0.9871 | 0.9871 | 0.9871 | 0.9871 | |
| | No log | 5.0 | 320 | 0.0390 | 0.9888 | 0.9888 | 0.9888 | 0.9888 | |
| | No log | 6.0 | 384 | 0.0364 | 0.9897 | 0.9897 | 0.9897 | 0.9897 | |
| | No log | 7.0 | 448 | 0.0345 | 0.9905 | 0.9905 | 0.9905 | 0.9905 | |
| | No log | 8.0 | 512 | 0.0334 | 0.9908 | 0.9908 | 0.9908 | 0.9908 | |
| | No log | 9.0 | 576 | 0.0334 | 0.9908 | 0.9908 | 0.9908 | 0.9908 | |
| | No log | 10.0 | 640 | 0.0324 | 0.9912 | 0.9912 | 0.9912 | 0.9912 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.28.1 |
| - Pytorch 1.13.0+cu117 |
| - Datasets 2.11.0 |
| - Tokenizers 0.11.6 |
|
|
