---
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[:5000]
      args: rb
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.26
---

<!-- 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: 3.1584
- Accuracy: 0.26

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 4.9434        | 0.99  | 31   | 4.8016          | 0.108    |
| 4.5209        | 1.98  | 62   | 4.3832          | 0.108    |
| 4.1573        | 2.98  | 93   | 3.9995          | 0.108    |
| 3.8211        | 4.0   | 125  | 3.6762          | 0.108    |
| 3.5876        | 4.99  | 156  | 3.4586          | 0.152    |
| 3.4453        | 5.98  | 187  | 3.3284          | 0.191    |
| 3.313         | 6.98  | 218  | 3.2432          | 0.21     |
| 3.2369        | 8.0   | 250  | 3.1993          | 0.223    |
| 3.2286        | 8.99  | 281  | 3.1712          | 0.23     |
| 3.1867        | 9.92  | 310  | 3.1584          | 0.26     |


### Framework versions

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