---
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: 1.0453
- Accuracy: 0.7794
- F1: 0.7715
- Recall: 0.7722
- Precision: 0.7752

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
| 2.2104        | 1.0   | 267  | 2.2272          | 0.3755   | 0.3160 | 0.3656 | 0.3611    |
| 1.6919        | 2.0   | 534  | 1.7563          | 0.4622   | 0.3974 | 0.4519 | 0.3981    |
| 1.3183        | 3.0   | 801  | 1.4686          | 0.5366   | 0.4834 | 0.5237 | 0.5364    |
| 1.0196        | 4.0   | 1068 | 1.2824          | 0.6183   | 0.5754 | 0.6094 | 0.5873    |
| 1.0655        | 5.0   | 1335 | 1.2136          | 0.6196   | 0.5822 | 0.6075 | 0.6142    |
| 0.8205        | 6.0   | 1602 | 1.0635          | 0.6778   | 0.6449 | 0.6687 | 0.6611    |
| 0.6309        | 7.0   | 1869 | 1.0256          | 0.7088   | 0.6798 | 0.6975 | 0.7004    |
| 0.4618        | 8.0   | 2136 | 0.9435          | 0.7435   | 0.7330 | 0.7373 | 0.7387    |
| 0.4057        | 9.0   | 2403 | 0.9192          | 0.7534   | 0.7403 | 0.7465 | 0.7507    |
| 0.2491        | 10.0  | 2670 | 0.9099          | 0.7596   | 0.7539 | 0.7510 | 0.7640    |
| 0.2548        | 11.0  | 2937 | 1.0901          | 0.7336   | 0.7305 | 0.7291 | 0.7475    |
| 0.0885        | 12.0  | 3204 | 1.0956          | 0.7447   | 0.7417 | 0.7387 | 0.7519    |
| 0.0988        | 13.0  | 3471 | 1.0585          | 0.7695   | 0.7623 | 0.7634 | 0.7641    |
| 0.1982        | 14.0  | 3738 | 1.0453          | 0.7794   | 0.7715 | 0.7722 | 0.7752    |
| 0.0966        | 15.0  | 4005 | 1.0914          | 0.7732   | 0.7676 | 0.7690 | 0.7706    |


### Framework versions

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