---
license: apache-2.0
base_model: openai/whisper-base.en
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: whisper-base.en-finetuned-gtzan
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: GTZAN
      type: marsyas/gtzan
      config: default
      split: train
      args: default
    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.en-finetuned-gtzan

This model is a fine-tuned version of [openai/whisper-base.en](https://huggingface.co/openai/whisper-base.en) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6266
- 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: 12
- eval_batch_size: 12
- 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: 18

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.7396        | 1.0   | 75   | 1.6061          | 0.56     |
| 0.8839        | 2.0   | 150  | 0.8286          | 0.77     |
| 0.7631        | 3.0   | 225  | 0.6353          | 0.81     |
| 0.4049        | 4.0   | 300  | 0.5840          | 0.82     |
| 0.3031        | 5.0   | 375  | 0.4069          | 0.88     |
| 0.3031        | 6.0   | 450  | 0.7152          | 0.81     |
| 0.2879        | 7.0   | 525  | 0.7061          | 0.85     |
| 0.0301        | 8.0   | 600  | 0.5691          | 0.89     |
| 0.0311        | 9.0   | 675  | 0.6153          | 0.88     |
| 0.0025        | 10.0  | 750  | 0.5463          | 0.88     |
| 0.0036        | 11.0  | 825  | 0.6017          | 0.89     |
| 0.0016        | 12.0  | 900  | 0.6859          | 0.85     |
| 0.0014        | 13.0  | 975  | 0.5887          | 0.89     |
| 0.0012        | 14.0  | 1050 | 0.6525          | 0.9      |
| 0.0011        | 15.0  | 1125 | 0.6289          | 0.89     |
| 0.0011        | 16.0  | 1200 | 0.6277          | 0.88     |
| 0.001         | 17.0  | 1275 | 0.6274          | 0.88     |
| 0.0611        | 18.0  | 1350 | 0.6266          | 0.88     |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.3
- Tokenizers 0.13.3