---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: whisper-tiny-finetuned-gtzan
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: GTZAN
      type: marsyas/gtzan
      config: all
      split: train
      args: all
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.89
---

<!-- 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: 0.7231
- Accuracy: 0.89

## 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: 5e-05
- train_batch_size: 6
- eval_batch_size: 6
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3867        | 1.0   | 150  | 0.4913          | 0.85     |
| 0.6883        | 2.0   | 300  | 0.9527          | 0.81     |
| 0.0056        | 3.0   | 450  | 0.6576          | 0.84     |
| 0.0021        | 4.0   | 600  | 0.7685          | 0.84     |
| 0.0007        | 5.0   | 750  | 0.7602          | 0.87     |
| 0.0005        | 6.0   | 900  | 0.8593          | 0.85     |
| 0.0005        | 7.0   | 1050 | 0.8438          | 0.84     |
| 0.0003        | 8.0   | 1200 | 0.6439          | 0.88     |
| 0.0003        | 9.0   | 1350 | 0.7370          | 0.88     |
| 0.0003        | 10.0  | 1500 | 0.7231          | 0.89     |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2