---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- gtzan
metrics:
- accuracy
model-index:
- name: whisper-tiny-finetuned-gtzan
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: gtzan
      type: gtzan
      config: all
      split: train
      args: all
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.865
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# whisper-tiny-finetuned-gtzan

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the gtzan dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5357
- Accuracy: 0.865

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| 1.8988        | 1.0   | 50   | 0.475    | 1.8064          |
| 1.2155        | 2.0   | 100  | 0.66     | 1.2221          |
| 0.9136        | 3.0   | 150  | 0.76     | 0.9259          |
| 0.7999        | 4.0   | 200  | 0.8      | 0.7412          |
| 0.4499        | 5.0   | 250  | 0.785    | 0.6758          |
| 0.2986        | 6.0   | 300  | 0.845    | 0.5601          |
| 0.2432        | 7.0   | 350  | 0.825    | 0.5678          |
| 0.1316        | 8.0   | 400  | 0.845    | 0.5153          |
| 0.1685        | 9.0   | 450  | 0.86     | 0.4840          |
| 0.1344        | 10.0  | 500  | 0.86     | 0.4803          |
| 0.0499        | 11.0  | 550  | 0.5167   | 0.855           |
| 0.0969        | 12.0  | 600  | 0.5370   | 0.85            |
| 0.0351        | 13.0  | 650  | 0.5022   | 0.86            |
| 0.0452        | 14.0  | 700  | 0.5289   | 0.855           |
| 0.0167        | 15.0  | 750  | 0.5357   | 0.865           |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1