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---
license: bsd-3-clause
base_model: MIT/ast-finetuned-audioset-10-10-0.4593
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: 0.5270
- 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3141 | 1.0 | 112 | 0.6444 | 0.8 |
| 0.3915 | 2.0 | 225 | 0.5292 | 0.85 |
| 0.2685 | 3.0 | 337 | 0.4638 | 0.85 |
| 0.0043 | 4.0 | 450 | 0.6904 | 0.88 |
| 0.124 | 5.0 | 562 | 0.5522 | 0.91 |
| 0.0002 | 6.0 | 675 | 0.4958 | 0.87 |
| 0.0003 | 7.0 | 787 | 0.5430 | 0.87 |
| 0.0001 | 8.0 | 900 | 0.5116 | 0.89 |
| 0.1202 | 9.0 | 1012 | 0.5194 | 0.88 |
| 0.0001 | 9.96 | 1120 | 0.5270 | 0.88 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
|