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---
license: apache-2.0
base_model: dima806/music_genres_classification
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: music_genres_classification-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: 0.87
---
<!-- 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. -->
# music_genres_classification-finetuned-gtzan
This model is a fine-tuned version of [dima806/music_genres_classification](https://huggingface.co/dima806/music_genres_classification) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0028
- Accuracy: 0.87
## 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: 5
- eval_batch_size: 5
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.12
- num_epochs: 15
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.5758 | 1.0 | 180 | 1.5756 | 0.52 |
| 1.079 | 2.0 | 360 | 1.2787 | 0.6 |
| 1.186 | 3.0 | 540 | 1.3863 | 0.58 |
| 0.9181 | 4.0 | 720 | 1.3967 | 0.64 |
| 0.4356 | 5.0 | 900 | 1.2449 | 0.67 |
| 0.4013 | 6.0 | 1080 | 1.2714 | 0.71 |
| 0.5518 | 7.0 | 1260 | 0.8282 | 0.8 |
| 0.4808 | 8.0 | 1440 | 1.3598 | 0.75 |
| 0.3608 | 9.0 | 1620 | 1.1908 | 0.8 |
| 0.181 | 10.0 | 1800 | 0.9824 | 0.83 |
| 0.0553 | 11.0 | 1980 | 1.0336 | 0.84 |
| 0.2445 | 12.0 | 2160 | 1.1085 | 0.83 |
| 0.0103 | 13.0 | 2340 | 1.1288 | 0.84 |
| 0.2437 | 14.0 | 2520 | 1.0183 | 0.85 |
| 0.0921 | 15.0 | 2700 | 1.0028 | 0.87 |
### Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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