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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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- accuracy |
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model-index: |
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- name: hubert-base-ls960-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: 0.84 |
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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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# hubert-base-ls960-finetuned-gtzan |
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This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on the GTZAN dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6527 |
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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: 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: 15 |
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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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| 2.1249 | 1.0 | 112 | 1.9377 | 0.43 | |
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| 1.6556 | 2.0 | 225 | 1.5867 | 0.47 | |
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| 1.2564 | 3.0 | 337 | 1.2670 | 0.56 | |
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| 1.0786 | 4.0 | 450 | 1.1080 | 0.59 | |
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| 0.895 | 5.0 | 562 | 0.8518 | 0.75 | |
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| 0.7177 | 6.0 | 675 | 1.0047 | 0.7 | |
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| 0.964 | 7.0 | 787 | 0.7430 | 0.75 | |
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| 0.4107 | 8.0 | 900 | 1.0347 | 0.71 | |
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| 0.4166 | 9.0 | 1012 | 0.5399 | 0.85 | |
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| 0.1234 | 10.0 | 1125 | 0.6266 | 0.83 | |
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| 0.0902 | 11.0 | 1237 | 0.6292 | 0.84 | |
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| 0.1211 | 12.0 | 1350 | 0.7393 | 0.84 | |
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| 0.4082 | 13.0 | 1462 | 0.6524 | 0.85 | |
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| 0.3442 | 14.0 | 1575 | 0.5732 | 0.86 | |
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| 0.0913 | 14.93 | 1680 | 0.6527 | 0.84 | |
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### Framework versions |
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- Transformers 4.31.0.dev0 |
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- Pytorch 1.13.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.13.3 |
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