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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: 0.7919463087248322
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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 audiofolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.4952
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- - Accuracy: 0.7919
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  ## Model description
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@@ -62,15 +62,19 @@ The following hyperparameters were used during training:
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: cosine
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  - lr_scheduler_warmup_ratio: 0.001
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- - num_epochs: 3
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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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- | No log | 0.9664 | 18 | 0.7078 | 0.7584 |
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- | No log | 1.9866 | 37 | 0.5109 | 0.7852 |
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- | No log | 2.8993 | 54 | 0.4952 | 0.7919 |
 
 
 
 
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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: 0.8691275167785235
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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: 0.3360
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+ - Accuracy: 0.8691
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  ## Model description
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: cosine
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  - lr_scheduler_warmup_ratio: 0.001
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+ - num_epochs: 7
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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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+ | No log | 0.9664 | 18 | 0.6860 | 0.7584 |
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+ | No log | 1.9866 | 37 | 0.4623 | 0.8020 |
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+ | No log | 2.9530 | 55 | 0.4069 | 0.8188 |
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+ | No log | 3.9732 | 74 | 0.3811 | 0.8356 |
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+ | No log | 4.9933 | 93 | 0.3542 | 0.8356 |
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+ | No log | 5.9597 | 111 | 0.3380 | 0.8658 |
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+ | No log | 6.7651 | 126 | 0.3360 | 0.8691 |
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  ### Framework versions
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