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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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datasets: |
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- common_voice_13_0 |
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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-breton-colab |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: common_voice_13_0 |
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type: common_voice_13_0 |
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config: br |
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split: test |
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args: br |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.5302549302549302 |
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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-breton-colab |
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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 common_voice_13_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0737 |
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- Wer: 0.5303 |
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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: 16 |
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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: 32 |
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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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 2.8658 | 2.68 | 400 | 1.2395 | 0.8972 | |
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| 0.8219 | 5.37 | 800 | 0.9454 | 0.6731 | |
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| 0.4743 | 8.05 | 1200 | 0.8880 | 0.6181 | |
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| 0.3224 | 10.74 | 1600 | 0.9330 | 0.6148 | |
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| 0.2415 | 13.42 | 2000 | 1.0494 | 0.5889 | |
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| 0.1904 | 16.11 | 2400 | 1.0328 | 0.5469 | |
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| 0.152 | 18.79 | 2800 | 1.0771 | 0.5625 | |
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| 0.1231 | 21.48 | 3200 | 0.9980 | 0.5598 | |
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| 0.0993 | 24.16 | 3600 | 1.0351 | 0.5317 | |
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| 0.0788 | 26.85 | 4000 | 1.0560 | 0.5381 | |
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| 0.0653 | 29.53 | 4400 | 1.0737 | 0.5303 | |
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### Framework versions |
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- Transformers 4.32.1 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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