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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-base-960h |
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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-960h-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: 0.87 |
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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-960h-finetuned-gtzan |
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This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co/facebook/wav2vec2-base-960h) on the GTZAN dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5055 |
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- Accuracy: 0.87 |
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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: 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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 2.2648 | 1.0 | 57 | 2.2400 | 0.15 | |
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| 2.167 | 2.0 | 114 | 2.1032 | 0.17 | |
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| 1.8573 | 3.0 | 171 | 1.7658 | 0.32 | |
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| 1.5347 | 4.0 | 228 | 1.6620 | 0.45 | |
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| 1.6134 | 5.0 | 285 | 1.5017 | 0.49 | |
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| 1.2903 | 6.0 | 342 | 1.4639 | 0.49 | |
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| 1.29 | 7.0 | 399 | 1.1893 | 0.66 | |
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| 1.1094 | 8.0 | 456 | 1.1425 | 0.67 | |
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| 1.1023 | 9.0 | 513 | 1.0173 | 0.72 | |
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| 0.9244 | 10.0 | 570 | 0.9069 | 0.79 | |
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| 0.7764 | 11.0 | 627 | 0.9314 | 0.74 | |
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| 0.6899 | 12.0 | 684 | 0.7919 | 0.78 | |
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| 0.6033 | 13.0 | 741 | 0.7145 | 0.8 | |
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| 0.4834 | 14.0 | 798 | 0.8896 | 0.76 | |
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| 0.4409 | 15.0 | 855 | 0.7083 | 0.82 | |
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| 0.3653 | 16.0 | 912 | 0.5633 | 0.83 | |
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| 0.3986 | 17.0 | 969 | 0.5475 | 0.89 | |
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| 0.2725 | 18.0 | 1026 | 0.5044 | 0.87 | |
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| 0.3569 | 19.0 | 1083 | 0.5044 | 0.85 | |
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| 0.2089 | 20.0 | 1140 | 0.5055 | 0.87 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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