---
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: whisper-base-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: 0.88
---

<!-- 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-base-finetuned-gtzan

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9387
- 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.589         | 1.0   | 57   | 1.4820          | 0.55     |
| 0.8965        | 2.0   | 114  | 0.8220          | 0.74     |
| 0.5723        | 3.0   | 171  | 0.5528          | 0.85     |
| 0.2395        | 4.0   | 228  | 0.6258          | 0.81     |
| 0.113         | 5.0   | 285  | 0.5659          | 0.82     |
| 0.2278        | 6.0   | 342  | 0.6686          | 0.83     |
| 0.0918        | 7.0   | 399  | 0.7184          | 0.86     |
| 0.0487        | 8.0   | 456  | 0.8123          | 0.87     |
| 0.0001        | 9.0   | 513  | 0.9589          | 0.86     |
| 0.0001        | 10.0  | 570  | 0.9387          | 0.88     |


### Framework versions

- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3