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---
library_name: transformers
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:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: GTZAN
type: marsyas/gtzan
config: all
split: train
args: all
metrics:
- name: Accuracy
type: accuracy
value: 0.9
---
<!-- 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: 0.4058
- 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: 15
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7832 | 1.0 | 113 | 0.5408 | 0.82 |
| 0.5775 | 2.0 | 226 | 0.7566 | 0.73 |
| 0.3894 | 3.0 | 339 | 0.4284 | 0.85 |
| 0.0137 | 4.0 | 452 | 0.4540 | 0.89 |
| 0.0961 | 5.0 | 565 | 0.9141 | 0.8 |
| 0.0454 | 6.0 | 678 | 0.7328 | 0.84 |
| 0.0028 | 7.0 | 791 | 1.1648 | 0.8 |
| 0.0001 | 8.0 | 904 | 0.4304 | 0.89 |
| 0.0001 | 9.0 | 1017 | 0.4028 | 0.9 |
| 0.0002 | 10.0 | 1130 | 0.4190 | 0.9 |
| 0.0001 | 11.0 | 1243 | 0.4039 | 0.9 |
| 0.0001 | 12.0 | 1356 | 0.4051 | 0.9 |
| 0.0001 | 13.0 | 1469 | 0.4056 | 0.9 |
| 0.0001 | 14.0 | 1582 | 0.4058 | 0.9 |
| 0.0001 | 15.0 | 1695 | 0.4058 | 0.9 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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