metadata
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
bird-call-classification
This model is a fine-tuned version of MIT/ast-finetuned-audioset-10-10-0.4593 on the 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