---
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: 0.4064
- 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: 16
- eval_batch_size: 16
- 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

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.988         | 1.0   | 57   | 1.4201          | 0.58     |
| 0.4825        | 2.0   | 114  | 0.7614          | 0.83     |
| 0.5993        | 3.0   | 171  | 0.5825          | 0.83     |
| 0.1427        | 4.0   | 228  | 0.4283          | 0.88     |
| 0.0461        | 5.0   | 285  | 0.3900          | 0.88     |
| 0.0438        | 6.0   | 342  | 0.4485          | 0.86     |
| 0.0171        | 7.0   | 399  | 0.3320          | 0.91     |
| 0.0182        | 8.0   | 456  | 0.3799          | 0.9      |
| 0.0066        | 9.0   | 513  | 0.3901          | 0.88     |
| 0.0077        | 10.0  | 570  | 0.4064          | 0.89     |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3