---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- accuracy
model-index:
- name: my_birdcall_model
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: audiofolder
      type: audiofolder
      config: rb
      split: train
      args: rb
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.09525756336876533
---

<!-- 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_birdcall_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: 4.1044
- Accuracy: 0.0953

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 4.925         | 1.0   | 153  | 4.9054          | 0.0194   |
| 4.6287        | 2.0   | 306  | 4.5973          | 0.0356   |
| 4.4783        | 3.0   | 459  | 4.4897          | 0.0478   |
| 4.3947        | 4.0   | 612  | 4.4000          | 0.0576   |
| 4.3246        | 5.0   | 765  | 4.3330          | 0.0681   |
| 4.2475        | 6.0   | 918  | 4.2791          | 0.0769   |
| 4.1713        | 7.0   | 1071 | 4.2455          | 0.0809   |
| 4.1255        | 8.0   | 1224 | 4.2108          | 0.0765   |
| 4.0992        | 9.0   | 1377 | 4.1849          | 0.0820   |
| 4.0128        | 10.0  | 1530 | 4.1478          | 0.0914   |
| 3.9299        | 11.0  | 1683 | 4.1618          | 0.0865   |
| 3.9218        | 12.0  | 1836 | 4.1216          | 0.0916   |
| 3.8447        | 13.0  | 1989 | 4.1305          | 0.0942   |
| 3.8873        | 14.0  | 2142 | 4.1120          | 0.0942   |
| 3.8107        | 15.0  | 2295 | 4.1044          | 0.0953   |


### Framework versions

- Transformers 4.38.0
- Pytorch 2.3.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0