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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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- 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: 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: 0.865
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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: 0.5357
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- Accuracy: 0.865
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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: 3e-05
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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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- gradient_accumulation_steps: 2
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- total_train_batch_size: 16
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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 | Accuracy | Validation Loss |
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|:-------------:|:-----:|:----:|:--------:|:---------------:|
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| 1.8988 | 1.0 | 50 | 0.475 | 1.8064 |
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| 1.2155 | 2.0 | 100 | 0.66 | 1.2221 |
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| 0.9136 | 3.0 | 150 | 0.76 | 0.9259 |
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| 0.7999 | 4.0 | 200 | 0.8 | 0.7412 |
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| 0.4499 | 5.0 | 250 | 0.785 | 0.6758 |
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| 0.2986 | 6.0 | 300 | 0.845 | 0.5601 |
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| 0.2432 | 7.0 | 350 | 0.825 | 0.5678 |
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| 0.1316 | 8.0 | 400 | 0.845 | 0.5153 |
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| 0.1685 | 9.0 | 450 | 0.86 | 0.4840 |
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| 0.1344 | 10.0 | 500 | 0.86 | 0.4803 |
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| 0.0499 | 11.0 | 550 | 0.5167 | 0.855 |
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| 0.0969 | 12.0 | 600 | 0.5370 | 0.85 |
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| 0.0351 | 13.0 | 650 | 0.5022 | 0.86 |
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| 0.0452 | 14.0 | 700 | 0.5289 | 0.855 |
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| 0.0167 | 15.0 | 750 | 0.5357 | 0.865 |
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### Framework versions
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- Transformers 4.34.1
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- Pytorch 2.1.0+cu118
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- Datasets 2.14.6
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- Tokenizers 0.14.1
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