| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: facebook/wav2vec2-large-960h |
| tags: |
| - generated_from_trainer |
| datasets: |
| - gigaspeech |
| metrics: |
| - wer |
| model-index: |
| - name: wav2vec_best |
| results: |
| - task: |
| name: Automatic Speech Recognition |
| type: automatic-speech-recognition |
| dataset: |
| name: gigaspeech |
| type: gigaspeech |
| config: xs |
| split: validation |
| args: xs |
| metrics: |
| - name: Wer |
| type: wer |
| value: 0.2950402352212937 |
| --- |
| |
| <!-- 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. --> |
|
|
| # wav2vec_best |
| |
| This model is a fine-tuned version of [facebook/wav2vec2-large-960h](https://huggingface.co/facebook/wav2vec2-large-960h) on the gigaspeech dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.7597 |
| - Wer: 0.2950 |
| |
| ## 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: 5e-05 |
| - train_batch_size: 1 |
| - eval_batch_size: 32 |
| - seed: 42 |
| - gradient_accumulation_steps: 8 |
| - total_train_batch_size: 8 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH 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: 200 |
| - num_epochs: 3 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Wer | |
| |:-------------:|:------:|:----:|:---------------:|:------:| |
| | 1.5437 | 1.0 | 1174 | 0.7964 | 0.3166 | |
| | 1.4351 | 2.0 | 2348 | 0.7771 | 0.3061 | |
| | 0.6393 | 2.9978 | 3519 | 0.7597 | 0.2950 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.50.3 |
| - Pytorch 2.6.0+cu124 |
| - Datasets 3.5.0 |
| - Tokenizers 0.21.1 |
| |
