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End of training

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  1. README.md +20 -19
  2. model.safetensors +1 -1
README.md CHANGED
@@ -22,7 +22,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.2708333333333333
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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 [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the audiofolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 2.0374
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- - Accuracy: 0.2708
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  ## Model description
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@@ -58,28 +58,29 @@ 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_ratio: 0.6
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- - num_epochs: 14
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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 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 2.4741 | 1.0 | 48 | 2.4767 | 0.1042 |
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- | 2.4794 | 2.0 | 96 | 2.4594 | 0.1042 |
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- | 2.4795 | 3.0 | 144 | 2.4242 | 0.1042 |
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- | 2.3636 | 4.0 | 192 | 2.3929 | 0.1042 |
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- | 2.2958 | 5.0 | 240 | 2.3036 | 0.1667 |
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- | 2.2177 | 6.0 | 288 | 2.1868 | 0.1771 |
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- | 1.9929 | 7.0 | 336 | 2.0746 | 0.2396 |
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- | 1.9842 | 8.0 | 384 | 2.0638 | 0.2292 |
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- | 1.934 | 9.0 | 432 | 2.0566 | 0.2292 |
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- | 1.7302 | 10.0 | 480 | 2.1105 | 0.2083 |
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- | 1.6971 | 11.0 | 528 | 1.9927 | 0.2292 |
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- | 1.4807 | 12.0 | 576 | 2.0434 | 0.2396 |
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- | 1.3496 | 13.0 | 624 | 2.0579 | 0.2708 |
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- | 1.3694 | 14.0 | 672 | 2.0374 | 0.2708 |
 
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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: 0.20833333333333334
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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 audiofolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.9825
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+ - Accuracy: 0.2083
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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_ratio: 0.1
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+ - num_epochs: 15
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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 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 2.4542 | 1.0 | 48 | 2.4501 | 0.1354 |
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+ | 2.499 | 2.0 | 96 | 2.4186 | 0.1042 |
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+ | 2.4441 | 3.0 | 144 | 2.3464 | 0.1875 |
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+ | 2.1364 | 4.0 | 192 | 2.2214 | 0.2083 |
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+ | 1.9561 | 5.0 | 240 | 2.1193 | 0.1771 |
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+ | 2.05 | 6.0 | 288 | 2.0221 | 0.1875 |
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+ | 1.7704 | 7.0 | 336 | 2.0434 | 0.1771 |
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+ | 1.8652 | 8.0 | 384 | 1.9728 | 0.1875 |
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+ | 1.77 | 9.0 | 432 | 1.9415 | 0.2292 |
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+ | 1.6381 | 10.0 | 480 | 2.0323 | 0.1562 |
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+ | 1.6316 | 11.0 | 528 | 1.9657 | 0.2292 |
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+ | 1.504 | 12.0 | 576 | 1.9644 | 0.1875 |
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+ | 1.3872 | 13.0 | 624 | 1.9719 | 0.2292 |
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+ | 1.3829 | 14.0 | 672 | 1.9794 | 0.1979 |
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+ | 1.3251 | 15.0 | 720 | 1.9825 | 0.2083 |
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  ### Framework versions
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