nithin04 commited on
Commit
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End of training

Browse files
README.md CHANGED
@@ -8,7 +8,7 @@ datasets:
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  metrics:
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  - accuracy
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  model-index:
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- - name: distilhubert-finetuned-gtzan
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  results:
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  - task:
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  name: Audio Classification
@@ -22,19 +22,19 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.81
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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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- [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/naganithin2004/huggingface/runs/ud7m62p6)
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- # distilhubert-finetuned-gtzan
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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: 0.6818
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- - Accuracy: 0.81
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  ## Model description
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@@ -54,29 +54,69 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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- - train_batch_size: 8
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- - eval_batch_size: 8
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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: 10
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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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- | 1.9467 | 1.0 | 113 | 1.8450 | 0.56 |
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- | 1.1922 | 2.0 | 226 | 1.2446 | 0.63 |
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- | 0.9442 | 3.0 | 339 | 0.9962 | 0.72 |
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- | 0.6935 | 4.0 | 452 | 0.8803 | 0.73 |
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- | 0.5568 | 5.0 | 565 | 0.8272 | 0.76 |
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- | 0.4095 | 6.0 | 678 | 0.6811 | 0.81 |
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- | 0.2956 | 7.0 | 791 | 0.6967 | 0.79 |
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- | 0.1496 | 8.0 | 904 | 0.6948 | 0.8 |
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- | 0.1861 | 9.0 | 1017 | 0.6542 | 0.8 |
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- | 0.1181 | 10.0 | 1130 | 0.6818 | 0.81 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  metrics:
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  - accuracy
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  model-index:
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+ - name: distilhubert-new-finetuned-gtzan
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  results:
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  - task:
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  name: Audio Classification
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.85
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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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+ [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/naganithin2004/huggingface/runs/i8in1y3p)
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+ # distilhubert-new-finetuned-gtzan
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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: 1.7615
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+ - Accuracy: 0.85
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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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: 50
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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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+ | 2.2914 | 1.0 | 57 | 2.2595 | 0.25 |
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+ | 2.1225 | 2.0 | 114 | 2.0265 | 0.57 |
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+ | 1.7631 | 3.0 | 171 | 1.6482 | 0.59 |
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+ | 1.3445 | 4.0 | 228 | 1.3380 | 0.62 |
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+ | 1.1548 | 5.0 | 285 | 1.0589 | 0.72 |
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+ | 0.9289 | 6.0 | 342 | 0.8541 | 0.76 |
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+ | 0.708 | 7.0 | 399 | 0.7628 | 0.79 |
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+ | 0.4497 | 8.0 | 456 | 0.7088 | 0.82 |
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+ | 0.4061 | 9.0 | 513 | 0.6118 | 0.85 |
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+ | 0.286 | 10.0 | 570 | 0.6684 | 0.79 |
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+ | 0.1739 | 11.0 | 627 | 0.5965 | 0.83 |
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+ | 0.1103 | 12.0 | 684 | 0.8414 | 0.81 |
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+ | 0.0922 | 13.0 | 741 | 0.5937 | 0.87 |
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+ | 0.0166 | 14.0 | 798 | 0.5786 | 0.86 |
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+ | 0.0075 | 15.0 | 855 | 0.7950 | 0.84 |
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+ | 0.0014 | 16.0 | 912 | 0.8492 | 0.87 |
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+ | 0.0006 | 17.0 | 969 | 1.2642 | 0.82 |
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+ | 0.0815 | 18.0 | 1026 | 1.1173 | 0.87 |
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+ | 0.0 | 19.0 | 1083 | 1.2181 | 0.86 |
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+ | 0.0 | 20.0 | 1140 | 1.6673 | 0.85 |
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+ | 0.0 | 21.0 | 1197 | 1.4749 | 0.86 |
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+ | 0.0611 | 22.0 | 1254 | 2.2533 | 0.82 |
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+ | 0.0978 | 23.0 | 1311 | 2.0092 | 0.86 |
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+ | 0.0 | 24.0 | 1368 | 2.3586 | 0.83 |
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+ | 0.0 | 25.0 | 1425 | 1.7617 | 0.86 |
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+ | 0.0 | 26.0 | 1482 | 1.7425 | 0.86 |
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+ | 0.0 | 27.0 | 1539 | 1.8418 | 0.85 |
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+ | 0.0 | 28.0 | 1596 | 1.6987 | 0.87 |
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+ | 0.0 | 29.0 | 1653 | 1.9399 | 0.85 |
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+ | 0.0 | 30.0 | 1710 | 2.4230 | 0.81 |
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+ | 0.0 | 31.0 | 1767 | 1.4312 | 0.88 |
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+ | 0.1807 | 32.0 | 1824 | 1.5278 | 0.87 |
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+ | 0.0 | 33.0 | 1881 | 1.3795 | 0.88 |
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+ | 0.0 | 34.0 | 1938 | 1.5051 | 0.88 |
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+ | 0.0 | 35.0 | 1995 | 1.6587 | 0.85 |
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+ | 0.0 | 36.0 | 2052 | 1.6256 | 0.86 |
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+ | 0.0 | 37.0 | 2109 | 1.7290 | 0.85 |
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+ | 0.0 | 38.0 | 2166 | 1.8676 | 0.87 |
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+ | 0.0 | 39.0 | 2223 | 1.8963 | 0.86 |
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+ | 0.166 | 40.0 | 2280 | 1.7057 | 0.85 |
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+ | 0.1293 | 41.0 | 2337 | 1.4235 | 0.87 |
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+ | 0.1491 | 42.0 | 2394 | 1.7916 | 0.85 |
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+ | 0.1416 | 43.0 | 2451 | 1.8634 | 0.85 |
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+ | 0.0 | 44.0 | 2508 | 1.6286 | 0.86 |
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+ | 0.0526 | 45.0 | 2565 | 1.6242 | 0.86 |
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+ | 0.0 | 46.0 | 2622 | 1.7576 | 0.85 |
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+ | 0.0 | 47.0 | 2679 | 1.7897 | 0.85 |
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+ | 0.0 | 48.0 | 2736 | 1.7571 | 0.85 |
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+ | 0.0018 | 49.0 | 2793 | 1.6993 | 0.85 |
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+ | 0.0 | 50.0 | 2850 | 1.7615 | 0.85 |
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  ### Framework versions
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