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# ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan

This model is a fine-tuned version of [MIT/ast-finetuned-audioset-10-10-0.4593](https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3496
- Accuracy: 0.85

## 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: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.9076        | 1.0   | 225   | 0.8234          | 0.75     |
| 0.3522        | 2.0   | 450   | 0.4291          | 0.9      |
| 0.4656        | 3.0   | 675   | 0.4656          | 0.83     |
| 0.2739        | 4.0   | 900   | 0.6314          | 0.9      |
| 0.575         | 5.0   | 1125  | 0.7786          | 0.85     |
| 0.4433        | 6.0   | 1350  | 1.1706          | 0.88     |
| 1.4075        | 7.0   | 1575  | 2.5171          | 0.83     |
| 0.1059        | 8.0   | 1800  | 1.5907          | 0.84     |
| 0.1521        | 9.0   | 2025  | 3.7424          | 0.72     |
| 0.5736        | 10.0  | 2250  | 2.0911          | 0.82     |
| 0.7552        | 11.0  | 2475  | 3.2042          | 0.81     |
| 0.166         | 12.0  | 2700  | 1.8762          | 0.86     |
| 0.0           | 13.0  | 2925  | 1.0614          | 0.91     |
| 1.2229        | 14.0  | 3150  | 3.0105          | 0.78     |
| 1.0135        | 15.0  | 3375  | 2.2024          | 0.85     |
| 0.098         | 16.0  | 3600  | 1.6070          | 0.87     |
| 0.0           | 17.0  | 3825  | 2.5323          | 0.82     |
| 0.0           | 18.0  | 4050  | 2.2202          | 0.86     |
| 0.0           | 19.0  | 4275  | 2.2681          | 0.85     |
| 0.0           | 20.0  | 4500  | 2.2394          | 0.86     |
| 1.8867        | 21.0  | 4725  | 4.2168          | 0.74     |
| 0.6094        | 22.0  | 4950  | 4.7781          | 0.72     |
| 0.3684        | 23.0  | 5175  | 2.6412          | 0.81     |
| 0.0           | 24.0  | 5400  | 2.8745          | 0.82     |
| 0.0           | 25.0  | 5625  | 2.9487          | 0.79     |
| 0.0           | 26.0  | 5850  | 2.5325          | 0.82     |
| 0.1597        | 27.0  | 6075  | 2.0327          | 0.85     |
| 0.0           | 28.0  | 6300  | 3.0062          | 0.84     |
| 0.0           | 29.0  | 6525  | 2.3104          | 0.8      |
| 0.0           | 30.0  | 6750  | 2.9985          | 0.83     |
| 0.0           | 31.0  | 6975  | 2.9385          | 0.82     |
| 0.0           | 32.0  | 7200  | 2.1102          | 0.87     |
| 0.0           | 33.0  | 7425  | 2.0060          | 0.86     |
| 1.1173        | 34.0  | 7650  | 1.9131          | 0.87     |
| 0.0           | 35.0  | 7875  | 2.4819          | 0.84     |
| 0.0           | 36.0  | 8100  | 2.0951          | 0.87     |
| 0.0           | 37.0  | 8325  | 1.9796          | 0.85     |
| 0.0           | 38.0  | 8550  | 2.0940          | 0.85     |
| 0.9059        | 39.0  | 8775  | 2.0714          | 0.85     |
| 0.0           | 40.0  | 9000  | 4.0729          | 0.75     |
| 0.0           | 41.0  | 9225  | 2.8627          | 0.83     |
| 0.0           | 42.0  | 9450  | 4.0389          | 0.76     |
| 0.0           | 43.0  | 9675  | 2.3248          | 0.85     |
| 0.6586        | 44.0  | 9900  | 4.9549          | 0.75     |
| 0.0           | 45.0  | 10125 | 3.3910          | 0.81     |
| 0.0           | 46.0  | 10350 | 3.9627          | 0.77     |
| 0.0           | 47.0  | 10575 | 3.4481          | 0.83     |
| 0.0           | 48.0  | 10800 | 2.7042          | 0.85     |
| 0.0           | 49.0  | 11025 | 2.8337          | 0.85     |
| 0.0           | 50.0  | 11250 | 2.4333          | 0.85     |
| 0.0           | 51.0  | 11475 | 2.6346          | 0.84     |
| 0.0           | 52.0  | 11700 | 1.8957          | 0.88     |
| 1.7162        | 53.0  | 11925 | 2.7006          | 0.85     |
| 0.0           | 54.0  | 12150 | 2.2261          | 0.86     |
| 0.0           | 55.0  | 12375 | 1.5562          | 0.89     |
| 0.0           | 56.0  | 12600 | 1.4557          | 0.91     |
| 0.0           | 57.0  | 12825 | 1.6862          | 0.89     |
| 0.0           | 58.0  | 13050 | 1.6635          | 0.9      |
| 0.0           | 59.0  | 13275 | 2.5130          | 0.85     |
| 0.0           | 60.0  | 13500 | 2.1794          | 0.84     |
| 0.0           | 61.0  | 13725 | 3.1630          | 0.82     |
| 0.0           | 62.0  | 13950 | 2.4938          | 0.84     |
| 0.0           | 63.0  | 14175 | 2.9464          | 0.82     |
| 0.0           | 64.0  | 14400 | 3.0567          | 0.81     |
| 0.0           | 65.0  | 14625 | 3.0951          | 0.82     |
| 0.0           | 66.0  | 14850 | 2.8673          | 0.82     |
| 0.0           | 67.0  | 15075 | 2.9092          | 0.82     |
| 0.0           | 68.0  | 15300 | 2.2521          | 0.85     |
| 0.0           | 69.0  | 15525 | 2.5049          | 0.82     |
| 0.0           | 70.0  | 15750 | 2.4376          | 0.84     |
| 0.0           | 71.0  | 15975 | 2.6660          | 0.82     |
| 0.0           | 72.0  | 16200 | 2.5182          | 0.86     |
| 0.0           | 73.0  | 16425 | 2.3814          | 0.85     |
| 0.0           | 74.0  | 16650 | 2.3093          | 0.85     |
| 0.0           | 75.0  | 16875 | 2.3014          | 0.85     |
| 0.0           | 76.0  | 17100 | 2.3845          | 0.86     |
| 0.0           | 77.0  | 17325 | 2.2978          | 0.85     |
| 0.0           | 78.0  | 17550 | 2.4215          | 0.85     |
| 0.7047        | 79.0  | 17775 | 2.3462          | 0.84     |
| 0.0           | 80.0  | 18000 | 2.3230          | 0.85     |
| 0.0           | 81.0  | 18225 | 2.3648          | 0.85     |
| 0.0           | 82.0  | 18450 | 2.2962          | 0.85     |
| 0.0           | 83.0  | 18675 | 2.4231          | 0.84     |
| 0.0           | 84.0  | 18900 | 2.2588          | 0.86     |
| 0.0           | 85.0  | 19125 | 2.4144          | 0.84     |
| 0.0           | 86.0  | 19350 | 2.4220          | 0.84     |
| 0.0           | 87.0  | 19575 | 2.3860          | 0.84     |
| 0.0           | 88.0  | 19800 | 2.3356          | 0.84     |
| 0.0           | 89.0  | 20025 | 2.3223          | 0.85     |
| 0.0           | 90.0  | 20250 | 2.3554          | 0.83     |
| 0.0           | 91.0  | 20475 | 2.3344          | 0.84     |
| 0.6906        | 92.0  | 20700 | 2.3568          | 0.85     |
| 0.0           | 93.0  | 20925 | 2.3905          | 0.84     |
| 0.0           | 94.0  | 21150 | 2.3920          | 0.85     |
| 0.0           | 95.0  | 21375 | 2.3935          | 0.85     |
| 0.0           | 96.0  | 21600 | 2.3392          | 0.85     |
| 0.0           | 97.0  | 21825 | 2.3437          | 0.85     |
| 0.0           | 98.0  | 22050 | 2.3434          | 0.85     |
| 0.0           | 99.0  | 22275 | 2.3503          | 0.85     |
| 0.0           | 100.0 | 22500 | 2.3496          | 0.85     |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0
- 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-10-10-0.4593", "model-index": [{"name": "ast-finetuned-audioset-10-10-0.4593-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": 0.85, "name": "Accuracy"}]}]}]}
transformers safetensors audio-spectrogram-transformer audio-classification generated_from_trainer dataset:marsyas/gtzan base_model:MIT/ast-finetuned-audioset-10-10-0.4593 license:bsd-3-clause model-index endpoints_compatible region:us