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constantinych
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distilhubert-finetuned_gtzan

Audio Classification
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hubert
Generated from Trainer
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  1. README.md +10 -10
  2. model.safetensors +1 -1
  3. runs/Jan20_15-27-19_victor-System-Product-Name/events.out.tfevents.1737376990.victor-System-Product-Name.28077.0 +2 -2
README.md CHANGED
@@ -23,7 +23,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.75
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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
@@ -33,8 +33,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the gtzan dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.8025
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- - Accuracy: 0.75
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 1.7782 | 1.0 | 113 | 1.7870 | 0.49 |
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- | 1.2942 | 2.0 | 226 | 1.3317 | 0.62 |
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- | 1.0869 | 3.0 | 339 | 1.0283 | 0.73 |
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- | 0.5358 | 4.0 | 452 | 0.9647 | 0.72 |
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- | 0.6048 | 5.0 | 565 | 0.7985 | 0.76 |
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- | 0.4135 | 6.0 | 678 | 0.8013 | 0.75 |
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- | 0.3721 | 7.0 | 791 | 0.8025 | 0.75 |
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  ### Framework versions
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.74
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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 [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the gtzan dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.8663
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+ - Accuracy: 0.74
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 1.7423 | 1.0 | 113 | 1.8224 | 0.43 |
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+ | 1.2488 | 2.0 | 226 | 1.3386 | 0.59 |
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+ | 1.0844 | 3.0 | 339 | 1.0498 | 0.7 |
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+ | 0.49 | 4.0 | 452 | 0.9295 | 0.72 |
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+ | 0.5017 | 5.0 | 565 | 0.8418 | 0.75 |
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+ | 0.3612 | 6.0 | 678 | 0.8414 | 0.75 |
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+ | 0.3045 | 7.0 | 791 | 0.8663 | 0.74 |
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  ### Framework versions
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