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End of training

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  1. README.md +11 -8
README.md CHANGED
@@ -1,10 +1,10 @@
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  ---
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- base_model: facebook/wav2vec2-large-960h
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  license: apache-2.0
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- metrics:
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- - wer
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  tags:
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  - generated_from_trainer
 
 
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  model-index:
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  - name: wav2vec2-base-cv-demo-google-colab
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  results: []
@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [facebook/wav2vec2-large-960h](https://huggingface.co/facebook/wav2vec2-large-960h) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.4229
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- - Wer: 0.7800
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  ## Model description
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@@ -43,15 +43,18 @@ The following hyperparameters were used during training:
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  - seed: 42
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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: 2
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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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- | 5.9165 | 1.1905 | 500 | 1.4229 | 0.7800 |
 
 
 
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  ### Framework versions
 
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  ---
 
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  license: apache-2.0
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+ base_model: facebook/wav2vec2-large-960h
 
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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-base-cv-demo-google-colab
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  results: []
 
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  This model is a fine-tuned version of [facebook/wav2vec2-large-960h](https://huggingface.co/facebook/wav2vec2-large-960h) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3575
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+ - Wer: 0.2805
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  ## Model description
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  - seed: 42
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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: 1000
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+ - num_epochs: 3
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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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+ | 8.951 | 0.7126 | 300 | 3.0660 | 1.0 |
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+ | 3.0514 | 1.4252 | 600 | 2.9228 | 1.0 |
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+ | 2.7598 | 2.1378 | 900 | 0.7960 | 0.5544 |
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+ | 0.7975 | 2.8504 | 1200 | 0.3575 | 0.2805 |
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  ### Framework versions