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--- |
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license: apache-2.0 |
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base_model: openai/whisper-tiny |
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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: whisper-tiny-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: 0.91 |
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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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# whisper-tiny-finetuned-gtzan |
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the GTZAN dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6420 |
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- Accuracy: 0.91 |
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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: 0.0001 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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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_steps: 10 |
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- num_epochs: 10 |
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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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| 1.9835 | 0.33 | 37 | 1.4610 | 0.62 | |
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| 1.5031 | 0.65 | 74 | 1.1531 | 0.63 | |
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| 1.1644 | 0.98 | 111 | 0.8526 | 0.73 | |
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| 0.9035 | 1.31 | 148 | 0.8748 | 0.69 | |
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| 0.7942 | 1.64 | 185 | 0.7811 | 0.78 | |
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| 0.8435 | 1.96 | 222 | 0.8262 | 0.7 | |
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| 0.5999 | 2.29 | 259 | 0.6450 | 0.72 | |
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| 0.6187 | 2.62 | 296 | 0.6616 | 0.79 | |
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| 0.6329 | 2.95 | 333 | 0.6479 | 0.81 | |
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| 0.3549 | 3.27 | 370 | 0.6246 | 0.78 | |
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| 0.3362 | 3.6 | 407 | 0.5348 | 0.81 | |
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| 0.3329 | 3.93 | 444 | 0.4657 | 0.85 | |
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| 0.2224 | 4.26 | 481 | 0.4433 | 0.89 | |
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| 0.208 | 4.58 | 518 | 0.6448 | 0.84 | |
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| 0.1983 | 4.91 | 555 | 0.6080 | 0.86 | |
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| 0.1736 | 5.24 | 592 | 0.6201 | 0.86 | |
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| 0.0976 | 5.57 | 629 | 0.6952 | 0.87 | |
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| 0.025 | 5.89 | 666 | 0.5872 | 0.9 | |
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| 0.0509 | 6.22 | 703 | 0.5845 | 0.91 | |
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| 0.1474 | 6.55 | 740 | 0.6800 | 0.89 | |
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| 0.0594 | 6.88 | 777 | 0.6280 | 0.87 | |
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| 0.0023 | 7.2 | 814 | 0.6850 | 0.88 | |
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| 0.0058 | 7.53 | 851 | 0.6766 | 0.89 | |
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| 0.023 | 7.86 | 888 | 0.8498 | 0.87 | |
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| 0.0272 | 8.19 | 925 | 0.7815 | 0.86 | |
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| 0.0011 | 8.51 | 962 | 0.6570 | 0.9 | |
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| 0.0012 | 8.84 | 999 | 0.6395 | 0.91 | |
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| 0.023 | 9.17 | 1036 | 0.6412 | 0.91 | |
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| 0.0009 | 9.5 | 1073 | 0.6416 | 0.91 | |
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| 0.001 | 9.82 | 1110 | 0.6420 | 0.91 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.3 |
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- Tokenizers 0.13.3 |
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