transformers tensorboard safetensors hubert audio-classification generated_from_trainer dataset:marsyas/gtzan base_model:chaouch/distilhubert-finetuned-gtzan license:apache-2.0 model-index endpoints_compatible region:us
---
license: apache-2.0
base_model: chaouch/distilhubert-finetuned-gtzan
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: distilhubert-finetuned-gtzan-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: 0.9666666666666667
---

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# distilhubert-finetuned-gtzan-finetuned-gtzan

This model is a fine-tuned version of [chaouch/distilhubert-finetuned-gtzan](https://huggingface.co/chaouch/distilhubert-finetuned-gtzan) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1733
- Accuracy: 0.9667

## 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: 0.0001
- train_batch_size: 6
- eval_batch_size: 6
- 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: 7
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.026         | 1.0   | 135  | 0.2289          | 0.9444   |
| 0.1351        | 2.0   | 270  | 0.1379          | 0.9778   |
| 0.01          | 3.0   | 405  | 0.2310          | 0.9667   |
| 0.0053        | 4.0   | 540  | 0.1727          | 0.9667   |
| 0.0002        | 5.0   | 675  | 0.1703          | 0.9667   |
| 0.0002        | 6.0   | 810  | 0.1722          | 0.9667   |
| 0.0002        | 7.0   | 945  | 0.1733          | 0.9667   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
