---
library_name: transformers
license: bsd-3-clause
base_model: MIT/ast-finetuned-audioset-10-10-0.4593
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: bird-call-classification
  results: []
datasets:
- kayalvizhi42/bird_calls
---

<!-- 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. -->

# bird-call-classification

This model is a fine-tuned version of [MIT/ast-finetuned-audioset-10-10-0.4593](https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593) on the [kayalvizhi42/bird_calls](https://huggingface.co/datasets/kayalvizhi42/bird_calls).
It achieves the following results on the evaluation set:
- Loss: 0.0735
- Accuracy: 0.9799
- Precision: 0.9579
- Recall: 1.0
- F1: 0.9785

## 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: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- 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
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log        | 1.0   | 50   | 0.2127          | 0.9497   | 0.9175    | 0.9780 | 0.9468 |
| No log        | 2.0   | 100  | 0.1252          | 0.9698   | 0.9474    | 0.9890 | 0.9677 |
| No log        | 3.0   | 150  | 0.1037          | 0.9749   | 0.9479    | 1.0    | 0.9733 |
| No log        | 4.0   | 200  | 0.0947          | 0.9698   | 0.9381    | 1.0    | 0.9681 |
| No log        | 5.0   | 250  | 0.0850          | 0.9799   | 0.9579    | 1.0    | 0.9785 |
| No log        | 6.0   | 300  | 0.0802          | 0.9799   | 0.9579    | 1.0    | 0.9785 |
| No log        | 7.0   | 350  | 0.0789          | 0.9799   | 0.9579    | 1.0    | 0.9785 |
| No log        | 8.0   | 400  | 0.0769          | 0.9799   | 0.9579    | 1.0    | 0.9785 |
| No log        | 9.0   | 450  | 0.0736          | 0.9799   | 0.9579    | 1.0    | 0.9785 |
| 0.1077        | 10.0  | 500  | 0.0735          | 0.9799   | 0.9579    | 1.0    | 0.9785 |


### Framework versions

- Transformers 4.48.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0