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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: 0.4936988936988937 |
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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: 1.2211 |
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- Wer: 0.4937 |
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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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 5.3288 | 1.34 | 400 | 1.7076 | 0.9809 | |
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| 1.2014 | 2.69 | 800 | 1.0803 | 0.7733 | |
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| 0.7687 | 4.03 | 1200 | 0.9806 | 0.6642 | |
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| 0.5539 | 5.38 | 1600 | 0.9914 | 0.6301 | |
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| 0.4456 | 6.72 | 2000 | 0.9797 | 0.6265 | |
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| 0.3586 | 8.07 | 2400 | 1.0354 | 0.5803 | |
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| 0.2922 | 9.41 | 2800 | 0.9996 | 0.5821 | |
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| 0.2628 | 10.76 | 3200 | 1.0250 | 0.5708 | |
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| 0.2284 | 12.1 | 3600 | 1.0865 | 0.5722 | |
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| 0.1908 | 13.45 | 4000 | 1.0674 | 0.5450 | |
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| 0.1732 | 14.79 | 4400 | 1.1775 | 0.5614 | |
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| 0.153 | 16.13 | 4800 | 1.1542 | 0.5435 | |
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| 0.14 | 17.48 | 5200 | 1.1807 | 0.5449 | |
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| 0.1302 | 18.82 | 5600 | 1.1679 | 0.5376 | |
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| 0.1142 | 20.17 | 6000 | 1.1441 | 0.5276 | |
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| 0.104 | 21.51 | 6400 | 1.2243 | 0.5355 | |
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| 0.0882 | 22.86 | 6800 | 1.1837 | 0.5316 | |
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| 0.0807 | 24.2 | 7200 | 1.1986 | 0.5132 | |
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| 0.0744 | 25.55 | 7600 | 1.2182 | 0.5108 | |
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| 0.0646 | 26.89 | 8000 | 1.2116 | 0.5047 | |
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| 0.0551 | 28.24 | 8400 | 1.2009 | 0.4948 | |
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| 0.0503 | 29.58 | 8800 | 1.2211 | 0.4937 | |
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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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