---
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- gtzan
metrics:
- accuracy
model-index:
- name: whisper-small-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: 0.91
---

<!-- 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-small-finetuned-gtzan

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the gtzan dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4896
- 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: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- 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 | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.292         | 1.0   | 100  | 1.3642          | 0.595    |
| 1.0263        | 2.0   | 200  | 0.9241          | 0.725    |
| 0.5906        | 3.0   | 300  | 0.9602          | 0.68     |
| 0.2665        | 4.0   | 400  | 0.8529          | 0.745    |
| 0.2222        | 5.0   | 500  | 0.6671          | 0.835    |
| 0.1649        | 6.0   | 600  | 0.4792          | 0.9      |
| 0.0018        | 7.0   | 700  | 0.7901          | 0.87     |
| 0.0303        | 8.0   | 800  | 0.4475          | 0.925    |
| 0.0011        | 9.0   | 900  | 0.5972          | 0.895    |
| 0.0008        | 10.0  | 1000 | 0.5501          | 0.9      |
| 0.0007        | 11.0  | 1100 | 0.5916          | 0.895    |
| 0.0007        | 12.0  | 1200 | 0.5719          | 0.9      |
| 0.0007        | 13.0  | 1300 | 0.5082          | 0.92     |
| 0.0007        | 14.0  | 1400 | 0.4954          | 0.905    |
| 0.0006        | 15.0  | 1500 | 0.4896          | 0.91     |


### Framework versions

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