| --- |
| license: apache-2.0 |
| base_model: facebook/wav2vec2-xls-r-300m |
| tags: |
| - generated_from_trainer |
| metrics: |
| - wer |
| model-index: |
| - name: wav2vec2-large-xls-r-300m-dysarthria |
| 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. --> |
|
|
| # wav2vec2-large-xls-r-300m-dysarthria |
|
|
| This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0615 |
| - Wer: 0.1764 |
|
|
| ## 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: 0.0003 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - gradient_accumulation_steps: 2 |
| - total_train_batch_size: 16 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 500 |
| - num_epochs: 30 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Wer | |
| |:-------------:|:-----:|:----:|:---------------:|:------:| |
| | 16.998 | 2.17 | 400 | 3.4205 | 1.0 | |
| | 3.6507 | 4.34 | 800 | 3.2819 | 1.0 | |
| | 3.2148 | 6.5 | 1200 | 3.0239 | 1.0 | |
| | 2.8464 | 8.67 | 1600 | 2.5810 | 1.0 | |
| | 2.3923 | 10.84 | 2000 | 2.2368 | 1.0 | |
| | 1.9358 | 13.01 | 2400 | 1.7072 | 1.0 | |
| | 1.5043 | 15.18 | 2800 | 1.3435 | 1.0 | |
| | 1.1169 | 17.34 | 3200 | 0.8979 | 0.9701 | |
| | 0.749 | 19.51 | 3600 | 0.5764 | 0.7490 | |
| | 0.4855 | 21.68 | 4000 | 0.2876 | 0.4763 | |
| | 0.2902 | 23.85 | 4400 | 0.1645 | 0.3379 | |
| | 0.198 | 26.02 | 4800 | 0.0988 | 0.2307 | |
| | 0.1358 | 28.18 | 5200 | 0.0615 | 0.1764 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.35.2 |
| - Pytorch 2.1.0+cu121 |
| - Datasets 2.16.1 |
| - Tokenizers 0.15.1 |
|
|
