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README.md
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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: 0.9
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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: 0.4744
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- Accuracy: 0.9
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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: 16
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- eval_batch_size: 16
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- seed: 42
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 32
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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: 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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| 0.0107 | 0.98 | 28 | 0.5000 | 0.86 |
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| 0.1932 | 2.0 | 57 | 0.6231 | 0.85 |
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| 0.0589 | 2.98 | 85 | 0.7759 | 0.81 |
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| 0.0475 | 4.0 | 114 | 0.4744 | 0.9 |
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| 0.0303 | 4.98 | 142 | 0.6446 | 0.88 |
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| 0.0037 | 6.0 | 171 | 0.4784 | 0.88 |
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| 0.0014 | 6.98 | 199 | 0.6325 | 0.86 |
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| 0.0015 | 8.0 | 228 | 0.6423 | 0.88 |
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| 0.0012 | 8.98 | 256 | 0.5485 | 0.89 |
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| 0.0231 | 9.82 | 280 | 0.5532 | 0.89 |
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### Framework versions
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- Transformers 4.32.0.dev0
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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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