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michaelsh
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distilhubert-finetuned-gtzan

Audio Classification
Transformers
PyTorch
hubert
Generated from Trainer
Inference Endpoints
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  1. README.md +63 -2
  2. config.json +1 -1
  3. gitattributes.txt +35 -0
  4. gitignore.txt +1 -0
  5. pytorch_model.bin +1 -1
  6. training_args.bin +1 -1
README.md CHANGED
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  ---
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  license: apache-2.0
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  tags:
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- - marsyas/gtzan
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  datasets:
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  - marsyas/gtzan
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  metrics:
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  model-index:
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  - name: distilhubert-finetuned-gtzan
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  results: []
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  license: apache-2.0
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  tags:
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+ - generated_from_trainer
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  datasets:
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  - marsyas/gtzan
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  metrics:
 
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  model-index:
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  - name: distilhubert-finetuned-gtzan
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  results: []
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+ ---
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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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+
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+ # distilhubert-finetuned-gtzan
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+
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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: 0.7058
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+ - Accuracy: 0.79
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 4
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+ - eval_batch_size: 4
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+ - seed: 42
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 8
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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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 1.7675 | 1.0 | 112 | 1.8184 | 0.42 |
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+ | 1.2504 | 2.0 | 225 | 1.3015 | 0.62 |
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+ | 1.0353 | 3.0 | 337 | 0.9890 | 0.72 |
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+ | 0.8318 | 4.0 | 450 | 0.8237 | 0.8 |
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+ | 0.4429 | 5.0 | 562 | 0.8123 | 0.78 |
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+ | 0.4286 | 6.0 | 675 | 0.6820 | 0.8 |
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+ | 0.2553 | 7.0 | 787 | 0.7826 | 0.78 |
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+ | 0.3022 | 8.0 | 900 | 0.6811 | 0.77 |
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+ | 0.1889 | 9.0 | 1012 | 0.6761 | 0.8 |
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+ | 0.1073 | 9.96 | 1120 | 0.7058 | 0.79 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.30.2
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.13.0
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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": "4.31.0.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": "4.30.2",
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  "use_weighted_layer_sum": false,
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  "vocab_size": 32
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  }
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