update model card README.md
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README.md
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- generated_from_trainer
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datasets:
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- marsyas/gtzan
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model-index:
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- name: distilhubert-finetuned-gtzan
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results:
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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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This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset.
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It achieves the following results on the evaluation set:
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- eval_runtime: 45.4165
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- eval_samples_per_second: 2.202
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- eval_steps_per_second: 0.154
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- epoch: 14.95
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- step: 213
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## Model description
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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:
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### Framework versions
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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: distilhubert-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: 0.77
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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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This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.8925
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- Accuracy: 0.77
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## Model description
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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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| 2.2921 | 0.98 | 14 | 2.2471 | 0.24 |
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| 2.1865 | 1.96 | 28 | 2.0565 | 0.45 |
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| 1.8969 | 2.95 | 42 | 1.7785 | 0.57 |
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| 1.659 | 4.0 | 57 | 1.5368 | 0.6 |
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| 1.4989 | 4.98 | 71 | 1.4186 | 0.66 |
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| 1.3204 | 5.96 | 85 | 1.2775 | 0.68 |
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| 1.2331 | 6.95 | 99 | 1.2127 | 0.69 |
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| 1.1486 | 8.0 | 114 | 1.1122 | 0.73 |
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| 1.0477 | 8.98 | 128 | 1.0672 | 0.73 |
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| 1.0297 | 9.96 | 142 | 1.0007 | 0.77 |
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| 0.9469 | 10.95 | 156 | 0.9488 | 0.77 |
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| 0.8761 | 12.0 | 171 | 0.9259 | 0.77 |
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| 0.8198 | 12.98 | 185 | 0.9115 | 0.78 |
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| 0.8503 | 13.96 | 199 | 0.8922 | 0.78 |
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| 0.8148 | 14.74 | 210 | 0.8925 | 0.77 |
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### Framework versions
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