| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: facebook/wav2vec2-xls-r-300m |
| tags: |
| - generated_from_trainer |
| datasets: |
| - common_voice_17_0 |
| metrics: |
| - wer |
| model-index: |
| - name: result_data-4 |
| results: |
| - task: |
| name: Automatic Speech Recognition |
| type: automatic-speech-recognition |
| dataset: |
| name: common_voice_17_0 |
| type: common_voice_17_0 |
| config: uk |
| split: test |
| args: uk |
| metrics: |
| - name: Wer |
| type: wer |
| value: 0.39399943390885933 |
| --- |
| |
| <!-- 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. --> |
|
|
| # result_data-4 |
| |
| This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice_17_0 dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.2488 |
| - Wer: 0.3940 |
| - Cer: 0.1776 |
|
|
| ## 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: 4.355619094803853e-05 |
| - train_batch_size: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - distributed_type: multi-GPU |
| - num_devices: 2 |
| - total_train_batch_size: 32 |
| - total_eval_batch_size: 32 |
| - optimizer: Use 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: 102 |
| - num_epochs: 7.0 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |
| |:-------------:|:------:|:----:|:---------------:|:------:|:------:| |
| | 0.9556 | 0.9099 | 1000 | 0.7514 | 0.7659 | 0.2976 | |
| | 0.4941 | 1.8198 | 2000 | 0.3987 | 0.5471 | 0.2174 | |
| | 0.3694 | 2.7298 | 3000 | 0.3282 | 0.4874 | 0.2005 | |
| | 0.3199 | 3.6397 | 4000 | 0.2846 | 0.4506 | 0.1901 | |
| | 0.2805 | 4.5496 | 5000 | 0.2716 | 0.4254 | 0.1855 | |
| | 0.2572 | 5.4595 | 6000 | 0.2622 | 0.4084 | 0.1810 | |
| | 0.2389 | 6.3694 | 7000 | 0.2483 | 0.4002 | 0.1791 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.49.0 |
| - Pytorch 2.6.0+cu124 |
| - Datasets 3.3.2 |
| - Tokenizers 0.21.0 |
| |
