---
library_name: transformers
base_model: leamac51
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
- f1
model-index:
- name: bsclass-finetuned-gtzan-1st-aprox-less-LR
  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: 0.915
    - name: F1
      type: f1
      value: 0.9147312393158322
---

<!-- 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. -->

# bsclass-finetuned-gtzan-1st-aprox-less-LR

This model is a fine-tuned version of [leamac51](https://huggingface.co/leamac51) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5240
- Accuracy: 0.915
- F1: 0.9147

## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 2.0897        | 1.0   | 100  | 2.0161          | 0.685    | 0.6827 |
| 1.6456        | 2.0   | 200  | 1.7330          | 0.66     | 0.6290 |
| 1.4091        | 3.0   | 300  | 1.3255          | 0.78     | 0.7732 |
| 1.1217        | 4.0   | 400  | 1.1425          | 0.82     | 0.8186 |
| 1.0118        | 5.0   | 500  | 0.9657          | 0.85     | 0.8524 |
| 0.7186        | 6.0   | 600  | 0.7777          | 0.86     | 0.8609 |
| 0.4308        | 7.0   | 700  | 0.5975          | 0.905    | 0.9040 |
| 0.451         | 8.0   | 800  | 0.5240          | 0.915    | 0.9147 |
| 0.3558        | 9.0   | 900  | 0.5822          | 0.885    | 0.8853 |
| 0.2556        | 10.0  | 1000 | 0.5207          | 0.905    | 0.9052 |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0