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# distilhubert-finetuned-gtzan-finetuned-gtzan

This model is a fine-tuned version of [distilhubert](https://huggingface.co/distilhubert) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0713
- Accuracy: 0.99

## 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- 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: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0972        | 1.0   | 113  | 0.0982          | 0.99     |
| 0.0478        | 2.0   | 226  | 0.0713          | 0.99     |


### Framework versions

- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0

{"tags": ["generated_from_trainer"], "datasets": ["marsyas/gtzan"], "metrics": ["accuracy"], "base_model": "distilhubert", "model-index": [{"name": "distilhubert-finetuned-gtzan-finetuned-gtzan", "results": [{"task": {"type": "audio-classification", "name": "Audio Classification"}, "dataset": {"name": "GTZAN", "type": "marsyas/gtzan", "config": "all", "split": "train", "args": "all"}, "metrics": [{"type": "accuracy", "value": 0.99, "name": "Accuracy"}]}]}]}
transformers pytorch hubert audio-classification generated_from_trainer dataset:marsyas/gtzan base_model:distilhubert model-index endpoints_compatible region:us