| --- |
| 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-5 |
| 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: 0.6674214548542315 |
| --- |
| |
| <!-- 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-5 |
| |
| 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: 0.4794 |
| - Wer: 0.6674 |
| - Cer: 0.2557 |
|
|
| ## 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: 8.442713223799316e-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: 84 |
| - num_epochs: 7.0 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |
| |:-------------:|:------:|:----:|:---------------:|:------:|:------:| |
| | 3.1606 | 0.9099 | 1000 | 3.1650 | 1.0 | 0.9920 | |
| | 1.2343 | 1.8198 | 2000 | 1.0356 | 0.9474 | 0.3937 | |
| | 0.7338 | 2.7298 | 3000 | 0.6668 | 0.7973 | 0.3038 | |
| | 0.6334 | 3.6397 | 4000 | 0.5813 | 0.7560 | 0.2852 | |
| | 0.5414 | 4.5496 | 5000 | 0.5283 | 0.6952 | 0.2675 | |
| | 0.5056 | 5.4595 | 6000 | 0.5042 | 0.6821 | 0.2633 | |
| | 0.4778 | 6.3694 | 7000 | 0.4794 | 0.6674 | 0.2557 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.49.0 |
| - Pytorch 2.6.0+cu124 |
| - Datasets 3.3.2 |
| - Tokenizers 0.21.0 |
| |
