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--- |
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license: apache-2.0 |
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base_model: facebook/hubert-base-ls960 |
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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: 0.88 |
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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: 0.7650 |
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- Accuracy: 0.88 |
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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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- 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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- 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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| 2.2258 | 1.0 | 225 | 1.9240 | 0.28 | |
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| 1.6083 | 2.0 | 450 | 1.4887 | 0.39 | |
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| 1.3983 | 3.0 | 675 | 1.3524 | 0.56 | |
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| 0.7368 | 4.0 | 900 | 1.3110 | 0.56 | |
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| 0.6121 | 5.0 | 1125 | 0.9572 | 0.72 | |
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| 0.1772 | 6.0 | 1350 | 0.8775 | 0.73 | |
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| 1.8666 | 7.0 | 1575 | 0.6078 | 0.82 | |
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| 0.091 | 8.0 | 1800 | 0.9999 | 0.76 | |
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| 0.0458 | 9.0 | 2025 | 0.7169 | 0.83 | |
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| 0.6817 | 10.0 | 2250 | 0.7614 | 0.86 | |
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| 0.7023 | 11.0 | 2475 | 0.9348 | 0.84 | |
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| 0.0047 | 12.0 | 2700 | 0.7222 | 0.88 | |
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| 0.0363 | 13.0 | 2925 | 0.7027 | 0.89 | |
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| 0.0073 | 14.0 | 3150 | 0.7440 | 0.88 | |
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| 0.0055 | 15.0 | 3375 | 0.7650 | 0.88 | |
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### Framework versions |
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- Transformers 4.38.0.dev0 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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