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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-xls-r-300m |
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tags: |
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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-large-xls-r-300m-dysarthria |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# wav2vec2-large-xls-r-300m-dysarthria |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0615 |
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- Wer: 0.1764 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0003 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 30 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 16.998 | 2.17 | 400 | 3.4205 | 1.0 | |
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| 3.6507 | 4.34 | 800 | 3.2819 | 1.0 | |
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| 3.2148 | 6.5 | 1200 | 3.0239 | 1.0 | |
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| 2.8464 | 8.67 | 1600 | 2.5810 | 1.0 | |
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| 2.3923 | 10.84 | 2000 | 2.2368 | 1.0 | |
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| 1.9358 | 13.01 | 2400 | 1.7072 | 1.0 | |
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| 1.5043 | 15.18 | 2800 | 1.3435 | 1.0 | |
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| 1.1169 | 17.34 | 3200 | 0.8979 | 0.9701 | |
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| 0.749 | 19.51 | 3600 | 0.5764 | 0.7490 | |
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| 0.4855 | 21.68 | 4000 | 0.2876 | 0.4763 | |
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| 0.2902 | 23.85 | 4400 | 0.1645 | 0.3379 | |
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| 0.198 | 26.02 | 4800 | 0.0988 | 0.2307 | |
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| 0.1358 | 28.18 | 5200 | 0.0615 | 0.1764 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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