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End of training

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  1. README.md +15 -15
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@@ -11,7 +11,7 @@ metrics:
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  - recall
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  - f1
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  model-index:
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- - name: distilhubert-finetuned-speech_commands-finetuned-gtzan
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  results:
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  - task:
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  name: Audio Classification
@@ -20,31 +20,31 @@ model-index:
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  name: audiofolder
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  type: audiofolder
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  config: default
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- split: test
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  args: default
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  metrics:
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  - name: Precision
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  type: precision
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- value: 0.9759184555734861
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  - name: Recall
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  type: recall
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- value: 0.9749126053876208
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  - name: F1
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  type: f1
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- value: 0.9749296122020006
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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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- # distilhubert-finetuned-speech_commands-finetuned-gtzan
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  This model is a fine-tuned version of [imrajeshkr/distilhubert-finetuned-speech_commands](https://huggingface.co/imrajeshkr/distilhubert-finetuned-speech_commands) on the audiofolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0934
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- - Precision: 0.9759
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- - Recall: 0.9749
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- - F1: 0.9749
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  ## Model description
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@@ -77,11 +77,11 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
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- | 0.2713 | 1.0 | 1216 | 0.2523 | 0.9172 | 0.9267 | 0.9166 |
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- | 0.137 | 2.0 | 2432 | 0.1119 | 0.9685 | 0.9667 | 0.9664 |
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- | 0.0295 | 3.0 | 3648 | 0.0977 | 0.9726 | 0.9703 | 0.9701 |
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- | 0.0037 | 4.0 | 4864 | 0.0956 | 0.9743 | 0.9733 | 0.9732 |
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- | 0.052 | 5.0 | 6080 | 0.0934 | 0.9759 | 0.9749 | 0.9749 |
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  ### Framework versions
 
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  - recall
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  - f1
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  model-index:
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+ - name: distilhubert-finetuned-speech_commands-finetuned-englishalphabets-classification
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  results:
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  - task:
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  name: Audio Classification
 
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  name: audiofolder
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  type: audiofolder
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  config: default
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+ split: validation
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  args: default
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  metrics:
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  - name: Precision
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  type: precision
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+ value: 0.9855379188712521
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  - name: Recall
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  type: recall
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+ value: 0.9827160493827161
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  - name: F1
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  type: f1
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+ value: 0.9825011002108681
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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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+ # distilhubert-finetuned-speech_commands-finetuned-englishalphabets-classification
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  This model is a fine-tuned version of [imrajeshkr/distilhubert-finetuned-speech_commands](https://huggingface.co/imrajeshkr/distilhubert-finetuned-speech_commands) on the audiofolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0563
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+ - Precision: 0.9855
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+ - Recall: 0.9827
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+ - F1: 0.9825
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
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+ | 0.2886 | 1.0 | 1216 | 0.2477 | 0.9098 | 0.9284 | 0.9127 |
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+ | 0.1426 | 2.0 | 2432 | 0.0792 | 0.9835 | 0.9802 | 0.9795 |
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+ | 0.0678 | 3.0 | 3648 | 0.0601 | 0.9827 | 0.9790 | 0.9780 |
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+ | 0.0062 | 4.0 | 4864 | 0.0601 | 0.9848 | 0.9815 | 0.9812 |
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+ | 0.027 | 5.0 | 6080 | 0.0563 | 0.9855 | 0.9827 | 0.9825 |
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  ### Framework versions