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KGSAGAR
/
distilhubert-finetuned-gtzan

Audio Classification
Transformers
PyTorch
hubert
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
KGSAGAR commited on
Commit
9231d03
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1 Parent(s): 12d62fc

End of training

Browse files
Files changed (4) hide show
  1. README.md +17 -16
  2. config.json +1 -1
  3. pytorch_model.bin +1 -1
  4. training_args.bin +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: 0.79
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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 GTZAN dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6990
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- - Accuracy: 0.79
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  ## Model description
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@@ -52,34 +52,35 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 4e-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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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 2.0716 | 1.0 | 113 | 1.9072 | 0.34 |
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- | 1.4457 | 2.0 | 226 | 1.3176 | 0.68 |
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- | 1.2214 | 3.0 | 339 | 0.9985 | 0.76 |
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- | 0.9552 | 4.0 | 452 | 0.8524 | 0.75 |
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- | 0.9033 | 5.0 | 565 | 0.7616 | 0.77 |
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- | 0.5696 | 6.0 | 678 | 0.7282 | 0.77 |
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- | 0.3836 | 7.0 | 791 | 0.7572 | 0.76 |
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- | 0.1939 | 8.0 | 904 | 0.7107 | 0.78 |
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- | 0.1817 | 9.0 | 1017 | 0.7017 | 0.77 |
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- | 0.2346 | 10.0 | 1130 | 0.6990 | 0.79 |
 
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  ### Framework versions
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- - Transformers 4.32.0.dev0
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  - Pytorch 2.0.1+cu118
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  - Datasets 2.14.4
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  - Tokenizers 0.13.3
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.86
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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: 0.5940
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+ - Accuracy: 0.86
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 6e-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: 11
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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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+ | 1.9604 | 1.0 | 113 | 1.8896 | 0.47 |
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+ | 0.9921 | 2.0 | 226 | 1.1632 | 0.65 |
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+ | 0.9314 | 3.0 | 339 | 0.9269 | 0.73 |
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+ | 0.7916 | 4.0 | 452 | 0.7033 | 0.84 |
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+ | 0.4223 | 5.0 | 565 | 0.6700 | 0.79 |
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+ | 0.2548 | 6.0 | 678 | 0.6467 | 0.85 |
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+ | 0.2854 | 7.0 | 791 | 0.6092 | 0.82 |
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+ | 0.1582 | 8.0 | 904 | 0.6272 | 0.86 |
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+ | 0.1024 | 9.0 | 1017 | 0.6225 | 0.82 |
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+ | 0.0345 | 10.0 | 1130 | 0.6064 | 0.84 |
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+ | 0.0671 | 11.0 | 1243 | 0.5940 | 0.86 |
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  ### Framework versions
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+ - Transformers 4.33.0.dev0
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  - Pytorch 2.0.1+cu118
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  - Datasets 2.14.4
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  - Tokenizers 0.13.3
config.json CHANGED
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  "num_hidden_layers": 2,
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  "pad_token_id": 0,
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  "torch_dtype": "float32",
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- "transformers_version": "4.32.0.dev0",
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  "use_weighted_layer_sum": false,
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  "vocab_size": 32
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  }
 
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  "num_hidden_layers": 2,
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  "pad_token_id": 0,
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  "torch_dtype": "float32",
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+ "transformers_version": "4.33.0.dev0",
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  "use_weighted_layer_sum": false,
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  "vocab_size": 32
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  }
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