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jcrkn
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wav2vec2-large-xls-r-300m-breton-colab_hyper2

Automatic Speech Recognition
Transformers
PyTorch
wav2vec2
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
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End of training

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  1. README.md +12 -12
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -22,7 +22,7 @@ model-index:
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  metrics:
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  - name: Wer
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  type: wer
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- value: 1.0
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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
@@ -32,8 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
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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: 3.0468
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- - Wer: 1.0
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  ## Model description
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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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- | 9.0648 | 0.67 | 200 | 3.1862 | 1.0 |
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- | 3.1613 | 1.34 | 400 | 3.1572 | 1.0 |
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- | 3.1565 | 2.02 | 600 | 3.1505 | 1.0 |
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- | 3.0857 | 2.69 | 800 | 3.0631 | 1.0 |
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- | 3.0627 | 3.36 | 1000 | 3.0647 | 1.0 |
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- | 3.0565 | 4.03 | 1200 | 3.0488 | 1.0 |
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- | 3.04 | 4.71 | 1400 | 3.0468 | 1.0 |
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  ### Framework versions
 
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  metrics:
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  - name: Wer
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  type: wer
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+ value: 0.7262145262145262
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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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  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: 0.9875
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+ - Wer: 0.7262
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  ## Model description
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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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+ | 7.2936 | 0.67 | 200 | 3.1142 | 1.0 |
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+ | 3.042 | 1.34 | 400 | 2.9484 | 1.0 |
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+ | 2.3704 | 2.02 | 600 | 1.6178 | 0.9658 |
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+ | 1.4289 | 2.69 | 800 | 1.2506 | 0.8708 |
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+ | 1.1529 | 3.36 | 1000 | 1.1119 | 0.7989 |
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+ | 0.9827 | 4.03 | 1200 | 1.0284 | 0.7575 |
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+ | 0.8429 | 4.71 | 1400 | 0.9875 | 0.7262 |
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  ### Framework versions
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