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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
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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: 0.4626
- Accuracy: 0.9
## 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: 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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6832 | 1.0 | 113 | 0.6136 | 0.79 |
| 0.3528 | 2.0 | 226 | 0.6350 | 0.77 |
| 0.178 | 3.0 | 339 | 0.7414 | 0.8 |
| 0.142 | 4.0 | 452 | 0.5234 | 0.84 |
| 0.1209 | 5.0 | 565 | 0.5176 | 0.88 |
| 0.0004 | 6.0 | 678 | 0.4160 | 0.88 |
| 0.0002 | 7.0 | 791 | 0.4798 | 0.9 |
| 0.0002 | 8.0 | 904 | 0.4693 | 0.89 |
| 0.1201 | 9.0 | 1017 | 0.4636 | 0.9 |
| 0.0002 | 10.0 | 1130 | 0.4626 | 0.9 |
### Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3