transformers tensorboard safetensors whisper audio-classification generated_from_trainer dataset:marsyas/gtzan base_model:openai/whisper-tiny license:apache-2.0 model-index endpoints_compatible region:us
---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: whisper-tiny-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: 0.91
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# whisper-tiny-finetuned-gtzan

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6410
- 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4155        | 1.0   | 225  | 1.1018          | 0.72     |
| 0.7952        | 2.0   | 450  | 1.0331          | 0.68     |
| 0.5194        | 3.0   | 675  | 0.5951          | 0.82     |
| 0.7917        | 4.0   | 900  | 0.5434          | 0.87     |
| 0.0147        | 5.0   | 1125 | 0.6317          | 0.86     |
| 0.006         | 6.0   | 1350 | 0.8828          | 0.85     |
| 0.0015        | 7.0   | 1575 | 0.7362          | 0.87     |
| 0.0009        | 8.0   | 1800 | 0.6188          | 0.91     |
| 0.0008        | 9.0   | 2025 | 0.6527          | 0.91     |
| 0.0007        | 10.0  | 2250 | 0.6410          | 0.91     |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
