| | --- |
| | library_name: transformers |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - wer |
| | model-index: |
| | - name: WMAC |
| | 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. --> |
| |
|
| | # WMAC |
| |
|
| | This model was trained from scratch on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.3746 |
| | - Wer: 60.4747 |
| |
|
| | ## 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: 32 |
| | - eval_batch_size: 8 |
| | - seed: 42 |
| | - 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: linear |
| | - lr_scheduler_warmup_steps: 700 |
| | - training_steps: 7000 |
| | - mixed_precision_training: Native AMP |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Wer | |
| | |:-------------:|:------:|:----:|:---------------:|:-------:| |
| | | 0.4011 | 0.4755 | 1000 | 0.4190 | 70.8256 | |
| | | 0.2792 | 0.9510 | 2000 | 0.2993 | 60.8256 | |
| | | 0.1901 | 1.4265 | 3000 | 0.2710 | 61.0217 | |
| | | 0.1361 | 1.9020 | 4000 | 0.2524 | 59.0402 | |
| | | 0.0730 | 2.3776 | 5000 | 0.2787 | 60.8772 | |
| | | 0.0592 | 2.8531 | 6000 | 0.2807 | 60.0826 | |
| | | 0.0213 | 3.3286 | 7000 | 0.3746 | 60.4747 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 5.2.0 |
| | - Pytorch 2.10.0+cu128 |
| | - Datasets 3.6.0 |
| | - Tokenizers 0.22.2 |
| |
|
