---
library_name: transformers
base_model: m3hrdadfi/wav2vec2-base-100k-gtzan-music-genres
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: wav2vec2-base-100k-gtzan-music-genres-finetuned-wav2vec2-ivan
  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: 0.98
---

<!-- 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. -->

# wav2vec2-base-100k-gtzan-music-genres-finetuned-wav2vec2-ivan

This model is a fine-tuned version of [m3hrdadfi/wav2vec2-base-100k-gtzan-music-genres](https://huggingface.co/m3hrdadfi/wav2vec2-base-100k-gtzan-music-genres) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2147
- Accuracy: 0.98

## 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use 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: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.0843        | 1.0   | 113  | 2.0074          | 0.82     |
| 1.7573        | 2.0   | 226  | 1.6688          | 0.89     |
| 1.5998        | 3.0   | 339  | 1.4663          | 0.86     |
| 1.3828        | 4.0   | 452  | 1.2642          | 0.96     |
| 1.1947        | 5.0   | 565  | 1.2147          | 0.98     |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0