---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- accuracy
model-index:
- name: my_custom2_model
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: audiofolder
      type: audiofolder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9166666666666666
---

<!-- 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. -->

# my_custom2_model

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4030
- Accuracy: 0.9167

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1798        | 1.0   | 6    | 0.4439          | 0.75     |
| 0.2051        | 2.0   | 12   | 0.5505          | 0.5833   |
| 0.1612        | 3.0   | 18   | 0.1884          | 0.9167   |
| 0.2032        | 4.0   | 24   | 0.2759          | 0.9167   |
| 0.1803        | 5.0   | 30   | 0.5196          | 0.8333   |
| 0.0478        | 6.0   | 36   | 0.3214          | 0.9167   |
| 0.1159        | 7.0   | 42   | 0.3311          | 0.9167   |
| 0.031         | 8.0   | 48   | 0.6261          | 0.8333   |
| 0.0263        | 9.0   | 54   | 0.3536          | 0.9167   |
| 0.2505        | 10.0  | 60   | 0.3637          | 0.9167   |
| 0.018         | 11.0  | 66   | 0.3721          | 0.9167   |
| 0.0167        | 12.0  | 72   | 0.6487          | 0.8333   |
| 0.0154        | 13.0  | 78   | 0.7422          | 0.8333   |
| 0.0144        | 14.0  | 84   | 0.7221          | 0.8333   |
| 0.0129        | 15.0  | 90   | 0.5876          | 0.8333   |
| 0.0123        | 16.0  | 96   | 0.4041          | 0.9167   |
| 0.0118        | 17.0  | 102  | 0.4000          | 0.9167   |
| 0.0115        | 18.0  | 108  | 0.4015          | 0.9167   |
| 0.0112        | 19.0  | 114  | 0.4025          | 0.9167   |
| 0.011         | 20.0  | 120  | 0.4030          | 0.9167   |


### Framework versions

- Transformers 4.50.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1