---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- recall
- precision
model-index:
- name: wav2vec2-base-music_genre_classifier-g4-firstseconds
  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. -->

# wav2vec2-base-music_genre_classifier-g4-firstseconds

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4970
- Accuracy: 0.8304
- F1: 0.8244
- Recall: 0.8262
- Precision: 0.8260

## 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: 12
- eval_batch_size: 12
- 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: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Recall | Precision |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:------:|:---------:|
| 1.1447        | 1.0   | 2393  | 1.2684          | 0.6524   | 0.6382 | 0.6533 | 0.6527    |
| 0.7302        | 2.0   | 4786  | 0.8886          | 0.7458   | 0.7421 | 0.7479 | 0.7637    |
| 0.521         | 3.0   | 7179  | 0.8755          | 0.7701   | 0.7686 | 0.7715 | 0.7934    |
| 0.3648        | 4.0   | 9572  | 1.0389          | 0.7731   | 0.7723 | 0.7673 | 0.7928    |
| 0.6132        | 5.0   | 11965 | 1.0694          | 0.7997   | 0.7955 | 0.7943 | 0.8170    |
| 0.6512        | 6.0   | 14358 | 1.2190          | 0.7886   | 0.7864 | 0.7864 | 0.7984    |
| 0.0851        | 7.0   | 16751 | 1.2496          | 0.8022   | 0.7959 | 0.7973 | 0.8082    |
| 0.0881        | 8.0   | 19144 | 1.2582          | 0.8127   | 0.8088 | 0.8105 | 0.8098    |
| 0.1063        | 9.0   | 21537 | 1.4087          | 0.8148   | 0.8119 | 0.8121 | 0.8176    |
| 0.4205        | 10.0  | 23930 | 1.4825          | 0.8055   | 0.8001 | 0.8019 | 0.8158    |
| 0.0478        | 11.0  | 26323 | 1.4240          | 0.8109   | 0.8023 | 0.8031 | 0.8082    |
| 0.0037        | 12.0  | 28716 | 1.3865          | 0.8248   | 0.8182 | 0.8199 | 0.8202    |
| 0.0236        | 13.0  | 31109 | 1.4570          | 0.8279   | 0.8230 | 0.8232 | 0.8250    |
| 0.0094        | 14.0  | 33502 | 1.4892          | 0.8289   | 0.8227 | 0.8248 | 0.8249    |
| 0.0002        | 15.0  | 35895 | 1.4970          | 0.8304   | 0.8244 | 0.8262 | 0.8260    |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3