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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-v2-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-v2-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: 0.7772 |
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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: 10 |
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- eval_batch_size: 10 |
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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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| 2.2028 | 1.0 | 90 | 2.1088 | 0.42 | |
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| 1.7214 | 2.0 | 180 | 1.6669 | 0.43 | |
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| 1.6141 | 3.0 | 270 | 1.5335 | 0.54 | |
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| 0.9971 | 4.0 | 360 | 1.1589 | 0.64 | |
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| 1.0174 | 5.0 | 450 | 0.9587 | 0.64 | |
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| 0.7295 | 6.0 | 540 | 0.8286 | 0.69 | |
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| 0.8034 | 7.0 | 630 | 0.8001 | 0.76 | |
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| 0.5709 | 8.0 | 720 | 0.9846 | 0.73 | |
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| 0.4724 | 9.0 | 810 | 0.6829 | 0.79 | |
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| 0.5161 | 10.0 | 900 | 0.9728 | 0.72 | |
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| 0.4247 | 11.0 | 990 | 0.7745 | 0.78 | |
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| 0.2696 | 12.0 | 1080 | 0.5330 | 0.87 | |
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| 0.1403 | 13.0 | 1170 | 0.7202 | 0.83 | |
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| 0.3434 | 14.0 | 1260 | 0.8506 | 0.82 | |
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| 0.2754 | 15.0 | 1350 | 0.6707 | 0.85 | |
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| 0.152 | 16.0 | 1440 | 0.8752 | 0.83 | |
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| 0.233 | 17.0 | 1530 | 0.5098 | 0.9 | |
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| 0.1169 | 18.0 | 1620 | 0.7069 | 0.86 | |
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| 0.1667 | 19.0 | 1710 | 0.7760 | 0.84 | |
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| 0.0691 | 20.0 | 1800 | 0.7772 | 0.84 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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