| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: XLS-R_53_english |
| 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. --> |
|
|
| # XLS-R_53_english |
|
|
| This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3430 |
| - Wer: 0.3033 |
|
|
| ## 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: 0.0001 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 1000 |
| - num_epochs: 30 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Wer | |
| |:-------------:|:-----:|:----:|:---------------:|:------:| |
| | 4.6589 | 1.65 | 500 | 3.1548 | 1.0 | |
| | 2.5363 | 3.3 | 1000 | 1.0250 | 0.8707 | |
| | 0.849 | 4.95 | 1500 | 0.3964 | 0.4636 | |
| | 0.4812 | 6.6 | 2000 | 0.3341 | 0.3907 | |
| | 0.3471 | 8.25 | 2500 | 0.3351 | 0.3659 | |
| | 0.2797 | 9.9 | 3000 | 0.3104 | 0.3475 | |
| | 0.2336 | 11.55 | 3500 | 0.3545 | 0.3419 | |
| | 0.2116 | 13.2 | 4000 | 0.3577 | 0.3353 | |
| | 0.1688 | 14.85 | 4500 | 0.3383 | 0.3302 | |
| | 0.1587 | 16.5 | 5000 | 0.3431 | 0.3235 | |
| | 0.1358 | 18.15 | 5500 | 0.3504 | 0.3209 | |
| | 0.1323 | 19.8 | 6000 | 0.3468 | 0.3191 | |
| | 0.115 | 21.45 | 6500 | 0.3331 | 0.3127 | |
| | 0.108 | 23.1 | 7000 | 0.3497 | 0.3099 | |
| | 0.0938 | 24.75 | 7500 | 0.3532 | 0.3091 | |
| | 0.0974 | 26.4 | 8000 | 0.3461 | 0.3086 | |
| | 0.0867 | 28.05 | 8500 | 0.3422 | 0.3054 | |
| | 0.0852 | 29.7 | 9000 | 0.3430 | 0.3033 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.17.0 |
| - Pytorch 1.12.1+cu113 |
| - Datasets 1.18.3 |
| - Tokenizers 0.12.1 |
| |
