apv53-fit
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distilhubert-finetuned-gtzan

Audio Classification

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apv53-fit commited on 23 days ago

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README.md +12 -12

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@@ -33,7 +33,7 @@ should probably proofread and complete it, then remove this comment. -->
 This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.6217
 - Accuracy: 0.8
 ## Model description
@@ -59,7 +59,7 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
 - lr_scheduler_type: linear
-- lr_scheduler_warmup_ratio: 0.3
 - num_epochs: 10
 - mixed_precision_training: Native AMP
@@ -67,16 +67,16 @@ The following hyperparameters were used during training:
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 2.2757        | 1.0   | 113  | 2.2336          | 0.26     |
-| 1.8835        | 2.0   | 226  | 1.8527          | 0.51     |
-| 1.5749        | 3.0   | 339  | 1.4378          | 0.67     |
-| 1.1165        | 4.0   | 452  | 1.0610          | 0.74     |
-| 0.9402        | 5.0   | 565  | 0.9178          | 0.79     |
-| 0.849         | 6.0   | 678  | 0.7739          | 0.78     |
-| 0.6661        | 7.0   | 791  | 0.7142          | 0.82     |
-| 0.4125        | 8.0   | 904  | 0.6851          | 0.82     |
-| 0.5223        | 9.0   | 1017 | 0.6216          | 0.83     |
-| 0.393         | 10.0  | 1130 | 0.6217          | 0.8      |
 ### Framework versions

 This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset.
 It achieves the following results on the evaluation set:
+- Loss: 0.7063
 - Accuracy: 0.8
 ## Model description
 - seed: 42
 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
 - lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.5
 - num_epochs: 10
 - mixed_precision_training: Native AMP
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 2.2776        | 1.0   | 113  | 2.2687          | 0.2      |
+| 2.0615        | 2.0   | 226  | 2.0397          | 0.55     |
+| 1.8286        | 3.0   | 339  | 1.7089          | 0.56     |
+| 1.4052        | 4.0   | 452  | 1.3901          | 0.66     |
+| 1.232         | 5.0   | 565  | 1.1751          | 0.69     |
+| 0.9855        | 6.0   | 678  | 0.9499          | 0.74     |
+| 0.8087        | 7.0   | 791  | 0.8492          | 0.75     |
+| 0.5098        | 8.0   | 904  | 0.7997          | 0.77     |
+| 0.5883        | 9.0   | 1017 | 0.7144          | 0.77     |
+| 0.4644        | 10.0  | 1130 | 0.7063          | 0.8      |
 ### Framework versions