weifeng1994 commited on
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End of training

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README.md ADDED
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+ ---
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+ license: bsd-3-clause
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+ base_model: MIT/ast-finetuned-audioset-10-10-0.4593
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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: ast-finetuned-audioset-10-10-0.4593-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: train
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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: 0.85
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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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+ # ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan
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+
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+ This model is a fine-tuned version of [MIT/ast-finetuned-audioset-10-10-0.4593](https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593) on the GTZAN dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.5926
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+ - Accuracy: 0.85
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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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+ - 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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+ | 1.0682 | 1.0 | 225 | 0.6954 | 0.73 |
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+ | 0.6581 | 2.0 | 450 | 0.7311 | 0.82 |
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+ | 0.382 | 3.0 | 675 | 0.6811 | 0.83 |
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+ | 0.023 | 4.0 | 900 | 0.5241 | 0.87 |
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+ | 0.1036 | 5.0 | 1125 | 0.7010 | 0.85 |
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+ | 0.0002 | 6.0 | 1350 | 0.6130 | 0.85 |
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+ | 0.2376 | 7.0 | 1575 | 0.6206 | 0.85 |
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+ | 0.0001 | 8.0 | 1800 | 0.6264 | 0.85 |
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+ | 0.0001 | 9.0 | 2025 | 0.5948 | 0.85 |
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+ | 0.0 | 10.0 | 2250 | 0.5926 | 0.85 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.37.1
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.16.1
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+ - Tokenizers 0.15.1
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