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---
license: bsd-3-clause
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# 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: 0.6230
- Accuracy: 0.89
## 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: 2
- eval_batch_size: 2
- 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
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.1198 | 1.0 | 450 | 1.8429 | 0.47 |
| 0.0005 | 2.0 | 900 | 1.6282 | 0.71 |
| 0.3129 | 3.0 | 1350 | 1.0553 | 0.73 |
| 0.0225 | 4.0 | 1800 | 0.9422 | 0.82 |
| 0.0025 | 5.0 | 2250 | 0.6008 | 0.85 |
| 0.0 | 6.0 | 2700 | 0.7194 | 0.86 |
| 0.0 | 7.0 | 3150 | 0.6268 | 0.89 |
| 0.0 | 8.0 | 3600 | 0.6372 | 0.89 |
| 0.0 | 9.0 | 4050 | 0.6167 | 0.89 |
| 0.0 | 10.0 | 4500 | 0.6230 | 0.89 |
### Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
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