---
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: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.88
---

<!-- 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: 0.8859
- Accuracy: 0.88

## 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: 8
- eval_batch_size: 8
- 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.7103        | 1.0   | 113  | 1.4757          | 0.57     |
| 0.8805        | 2.0   | 226  | 0.8030          | 0.74     |
| 0.7231        | 3.0   | 339  | 0.4844          | 0.88     |
| 0.9119        | 4.0   | 452  | 0.6392          | 0.79     |
| 0.2952        | 5.0   | 565  | 0.5729          | 0.83     |
| 0.1099        | 6.0   | 678  | 0.5263          | 0.83     |
| 0.1363        | 7.0   | 791  | 0.4978          | 0.91     |
| 0.0021        | 8.0   | 904  | 0.6480          | 0.89     |
| 0.0413        | 9.0   | 1017 | 0.7381          | 0.87     |
| 0.0023        | 10.0  | 1130 | 0.6896          | 0.9      |
| 0.0006        | 11.0  | 1243 | 0.7574          | 0.89     |
| 0.1621        | 12.0  | 1356 | 0.8407          | 0.88     |
| 0.0005        | 13.0  | 1469 | 0.7967          | 0.89     |
| 0.0005        | 14.0  | 1582 | 0.7795          | 0.89     |
| 0.0004        | 15.0  | 1695 | 0.7795          | 0.9      |
| 0.0003        | 16.0  | 1808 | 0.9152          | 0.87     |
| 0.0003        | 17.0  | 1921 | 0.8594          | 0.88     |
| 0.0003        | 18.0  | 2034 | 0.8481          | 0.88     |
| 0.0003        | 19.0  | 2147 | 0.8471          | 0.88     |
| 0.0545        | 20.0  | 2260 | 0.8859          | 0.88     |


### Framework versions

- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3