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update model card README.md
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README.md
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---
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license: apache-2.0
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base_model: facebook/wav2vec2-base
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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: wav2vec2-base-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: train
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split: train
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args: train
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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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<!-- 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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# wav2vec2-base-finetuned-gtzan
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the GTZAN dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.8879
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- Accuracy: 0.84
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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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: 17
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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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| 1.9838 | 1.0 | 113 | 1.8627 | 0.37 |
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| 1.6128 | 2.0 | 226 | 1.5998 | 0.48 |
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| 1.0259 | 3.0 | 339 | 1.3821 | 0.57 |
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| 1.2766 | 4.0 | 452 | 1.1708 | 0.66 |
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| 0.6014 | 5.0 | 565 | 0.7257 | 0.77 |
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| 0.5815 | 6.0 | 678 | 1.0738 | 0.68 |
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| 0.7664 | 7.0 | 791 | 0.7244 | 0.8 |
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| 0.2303 | 8.0 | 904 | 0.5838 | 0.84 |
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| 0.4829 | 9.0 | 1017 | 0.5741 | 0.87 |
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| 0.0859 | 10.0 | 1130 | 0.6199 | 0.83 |
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| 0.2983 | 11.0 | 1243 | 0.8117 | 0.84 |
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| 0.0642 | 12.0 | 1356 | 0.5938 | 0.88 |
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| 0.0688 | 13.0 | 1469 | 0.9978 | 0.84 |
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| 0.1542 | 14.0 | 1582 | 0.7437 | 0.85 |
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| 0.0117 | 15.0 | 1695 | 0.9100 | 0.84 |
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| 0.039 | 16.0 | 1808 | 0.7757 | 0.85 |
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| 0.0661 | 17.0 | 1921 | 0.8879 | 0.84 |
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### Framework versions
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- Transformers 4.31.0
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- Pytorch 2.0.1
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- Datasets 2.14.0
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- Tokenizers 0.13.3
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