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End of training

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README.md CHANGED
@@ -24,7 +24,7 @@ model-index:
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  metrics:
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  - name: Wer
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  type: wer
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- value: 98.78707976268953
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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
@@ -34,8 +34,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the audiofolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 2.5330
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- - Wer: 98.7871
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  ## Model description
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@@ -54,7 +54,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 1e-05
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  - train_batch_size: 16
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  - eval_batch_size: 8
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  - seed: 42
@@ -66,12 +66,12 @@ The following hyperparameters were used during training:
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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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- | 0.0573 | 13.89 | 1000 | 2.1023 | 109.3738 |
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- | 0.0122 | 27.78 | 2000 | 2.3627 | 66.3810 |
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- | 0.0088 | 41.67 | 3000 | 2.4397 | 89.5320 |
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- | 0.0072 | 55.56 | 4000 | 2.5330 | 98.7871 |
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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: 74.31180859274504
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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 [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the audiofolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 2.8726
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+ - Wer: 74.3118
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 1.25e-05
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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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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Wer |
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+ |:-------------:|:-----:|:----:|:---------------:|:-------:|
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+ | 0.0539 | 13.89 | 1000 | 2.3264 | 87.0594 |
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+ | 0.0116 | 27.78 | 2000 | 2.5778 | 91.6517 |
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+ | 0.0072 | 41.67 | 3000 | 2.8216 | 76.4729 |
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+ | 0.0074 | 55.56 | 4000 | 2.8726 | 74.3118 |
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  ### Framework versions
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