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saxenagauravhf
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distilhubert-finetuned-gtzan

Audio Classification
Transformers
Safetensors
hubert
Generated from Trainer
Eval Results
Inference Endpoints
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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: ntu-spml/distilhubert
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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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+ - 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
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+ type: audio-classification
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+ dataset:
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+ name: GTZAN
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+ type: marsyas/gtzan
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+ config: all
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+ split: None
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+ args: all
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.84
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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: 0.7755
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+ - Accuracy: 0.84
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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: 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: 20
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+ - mixed_precision_training: Native AMP
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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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+ | 2.2322 | 1.0 | 57 | 2.1521 | 0.37 |
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+ | 1.7413 | 2.0 | 114 | 1.6606 | 0.47 |
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+ | 1.3543 | 3.0 | 171 | 1.2698 | 0.69 |
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+ | 0.9436 | 4.0 | 228 | 1.0440 | 0.71 |
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+ | 0.7976 | 5.0 | 285 | 0.8338 | 0.79 |
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+ | 0.6615 | 6.0 | 342 | 0.6933 | 0.84 |
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+ | 0.5743 | 7.0 | 399 | 0.6180 | 0.84 |
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+ | 0.4349 | 8.0 | 456 | 0.5931 | 0.84 |
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+ | 0.2949 | 9.0 | 513 | 0.5794 | 0.85 |
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+ | 0.2274 | 10.0 | 570 | 0.5901 | 0.84 |
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+ | 0.1067 | 11.0 | 627 | 0.6496 | 0.81 |
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+ | 0.104 | 12.0 | 684 | 0.6921 | 0.82 |
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+ | 0.0781 | 13.0 | 741 | 0.6653 | 0.83 |
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+ | 0.0245 | 14.0 | 798 | 0.6621 | 0.84 |
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+ | 0.0144 | 15.0 | 855 | 0.7015 | 0.82 |
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+ | 0.0104 | 16.0 | 912 | 0.7109 | 0.85 |
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+ | 0.007 | 17.0 | 969 | 0.7472 | 0.84 |
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+ | 0.0163 | 18.0 | 1026 | 0.7603 | 0.86 |
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+ | 0.0039 | 19.0 | 1083 | 0.7710 | 0.85 |
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+ | 0.0035 | 20.0 | 1140 | 0.7755 | 0.84 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.43.0.dev0
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+ - Pytorch 2.3.1+cu118
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
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