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# ast-finetuned-audioset-10-10-0.450-finetuned-gtzan

This model is a fine-tuned version of [MIT/ast-finetuned-audioset-10-10-0.450](https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.450) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4457
- 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: 16
- eval_batch_size: 16
- 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: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5804        | 1.0   | 57   | 0.5356          | 0.84     |
| 0.2655        | 2.0   | 114  | 0.5664          | 0.76     |
| 0.1767        | 3.0   | 171  | 0.3925          | 0.88     |
| 0.4169        | 4.0   | 228  | 0.8874          | 0.78     |
| 0.0685        | 5.0   | 285  | 0.6067          | 0.83     |
| 0.0725        | 6.0   | 342  | 0.5612          | 0.81     |
| 0.1003        | 7.0   | 399  | 0.6928          | 0.82     |
| 0.004         | 8.0   | 456  | 0.4814          | 0.86     |
| 0.0122        | 9.0   | 513  | 0.6141          | 0.86     |
| 0.0009        | 10.0  | 570  | 0.4017          | 0.91     |
| 0.0828        | 11.0  | 627  | 0.4937          | 0.88     |
| 0.0025        | 12.0  | 684  | 0.8455          | 0.82     |
| 0.0005        | 13.0  | 741  | 0.4439          | 0.89     |
| 0.0001        | 14.0  | 798  | 0.4956          | 0.87     |
| 0.0001        | 15.0  | 855  | 0.4362          | 0.88     |
| 0.0001        | 16.0  | 912  | 0.4146          | 0.89     |
| 0.0299        | 17.0  | 969  | 0.4241          | 0.9      |
| 0.0001        | 18.0  | 1026 | 0.4375          | 0.87     |
| 0.0001        | 19.0  | 1083 | 0.4502          | 0.88     |
| 0.0001        | 20.0  | 1140 | 0.4457          | 0.88     |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "bsd-3-clause", "tags": ["generated_from_trainer"], "datasets": ["marsyas/gtzan"], "metrics": ["accuracy"], "base_model": "MIT/ast-finetuned-audioset-10-10-0.450", "model-index": [{"name": "ast-finetuned-audioset-10-10-0.450-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": 0.88, "name": "Accuracy"}]}]}]}
transformers tensorboard safetensors audio-spectrogram-transformer audio-classification generated_from_trainer dataset:marsyas/gtzan base_model:MIT/ast-finetuned-audioset-10-10-0.450 license:bsd-3-clause model-index endpoints_compatible region:us