---
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: whisper-small-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: 0.92
---

<!-- 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: 0.3487
- Accuracy: 0.92

## 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: 4e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- 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: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4671        | 1.0   | 112  | 0.9088          | 0.74     |
| 0.6277        | 2.0   | 225  | 0.6298          | 0.8      |
| 0.446         | 3.0   | 337  | 0.4495          | 0.86     |
| 0.19          | 4.0   | 450  | 0.3389          | 0.91     |
| 0.2302        | 5.0   | 562  | 0.2954          | 0.93     |
| 0.0031        | 6.0   | 675  | 0.3213          | 0.94     |
| 0.0021        | 6.97  | 784  | 0.3487          | 0.92     |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1