---
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: 0.91
---

<!-- 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: 0.6142
- Accuracy: 0.91

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.7559        | 1.0   | 113  | 1.6022          | 0.57     |
| 0.9793        | 2.0   | 226  | 0.9895          | 0.7      |
| 0.8508        | 3.0   | 339  | 0.6379          | 0.78     |
| 0.5114        | 4.0   | 452  | 0.8367          | 0.72     |
| 0.115         | 5.0   | 565  | 0.4465          | 0.88     |
| 0.0239        | 6.0   | 678  | 0.5796          | 0.85     |
| 0.2095        | 7.0   | 791  | 0.6141          | 0.87     |
| 0.0019        | 8.0   | 904  | 0.5765          | 0.88     |
| 0.0012        | 9.0   | 1017 | 0.5393          | 0.87     |
| 0.0013        | 10.0  | 1130 | 0.5126          | 0.92     |
| 0.0008        | 11.0  | 1243 | 0.4751          | 0.91     |
| 0.0006        | 12.0  | 1356 | 0.5002          | 0.91     |
| 0.0005        | 13.0  | 1469 | 0.4905          | 0.91     |
| 0.0006        | 14.0  | 1582 | 0.5577          | 0.91     |
| 0.0004        | 15.0  | 1695 | 0.6326          | 0.9      |
| 0.0004        | 16.0  | 1808 | 0.6188          | 0.92     |
| 0.0004        | 17.0  | 1921 | 0.6420          | 0.91     |
| 0.0003        | 18.0  | 2034 | 0.5999          | 0.91     |
| 0.0003        | 19.0  | 2147 | 0.6105          | 0.91     |
| 0.0003        | 20.0  | 2260 | 0.6142          | 0.91     |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu118
- Datasets 2.19.2
- Tokenizers 0.19.1