---
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: 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-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: 0.3412
- 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.5696        | 0.99  | 56   | 1.3573          | 0.62     |
| 0.9913        | 2.0   | 113  | 0.7820          | 0.77     |
| 0.4771        | 2.99  | 169  | 0.4873          | 0.84     |
| 0.4411        | 4.0   | 226  | 0.3367          | 0.91     |
| 0.1615        | 4.99  | 282  | 0.3412          | 0.92     |
| 0.1339        | 6.0   | 339  | 0.4125          | 0.91     |
| 0.0331        | 6.99  | 395  | 0.4773          | 0.89     |
| 0.0382        | 8.0   | 452  | 0.4282          | 0.88     |
| 0.049         | 8.99  | 508  | 0.4634          | 0.9      |
| 0.0312        | 9.91  | 560  | 0.4444          | 0.9      |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0