| --- |
| library_name: transformers |
| tags: |
| - generated_from_trainer |
| metrics: |
| - wer |
| model-index: |
| - name: WMACv2 |
| 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. --> |
|
|
| # WMACv2 |
|
|
| This model was trained from scratch on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.2606 |
| - Wer: 41.3106 |
|
|
| ## 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: 2.5e-05 |
| - train_batch_size: 8 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 32 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: cosine |
| - lr_scheduler_warmup_steps: 650 |
| - training_steps: 5000 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Wer | |
| |:-------------:|:------:|:----:|:---------------:|:-------:| |
| | 1.5465 | 0.4757 | 1000 | 0.4199 | 54.1280 | |
| | 1.0508 | 0.9514 | 2000 | 0.2911 | 43.9422 | |
| | 0.6641 | 1.4267 | 3000 | 0.2649 | 44.7884 | |
| | 0.4569 | 1.9024 | 4000 | 0.2369 | 41.4448 | |
| | 0.2753 | 2.3777 | 5000 | 0.2606 | 41.3106 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 5.2.0 |
| - Pytorch 2.10.0+cu128 |
| - Datasets 3.6.0 |
| - Tokenizers 0.22.2 |
| |
