| --- |
| tags: |
| - generated_from_trainer |
| metrics: |
| - wer |
| model-index: |
| - name: Model_G_P |
| 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. --> |
|
|
| # Model_G_P |
|
|
| This model was trained from scratch on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 2.4719 |
| - Wer: 0.5613 |
| - Cer: 0.2386 |
|
|
| ## 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: 0.0003 |
| - train_batch_size: 16 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - gradient_accumulation_steps: 2 |
| - total_train_batch_size: 32 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 500 |
| - num_epochs: 30 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |
| |:-------------:|:-----:|:----:|:---------------:|:------:|:------:| |
| | 0.447 | 4.17 | 400 | 2.1407 | 0.6004 | 0.2516 | |
| | 0.4338 | 8.33 | 800 | 2.1920 | 0.6033 | 0.2505 | |
| | 0.3209 | 12.5 | 1200 | 2.2978 | 0.6089 | 0.2601 | |
| | 0.2327 | 16.67 | 1600 | 2.3510 | 0.5871 | 0.2459 | |
| | 0.1735 | 20.83 | 2000 | 2.3828 | 0.5890 | 0.2480 | |
| | 0.1344 | 25.0 | 2400 | 2.3782 | 0.5647 | 0.2399 | |
| | 0.0909 | 29.17 | 2800 | 2.4719 | 0.5613 | 0.2386 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.31.0 |
| - Pytorch 2.0.1+cu117 |
| - Datasets 1.18.3 |
| - Tokenizers 0.13.3 |
|
|
