metadata
license: bsd-3-clause
base_model: MIT/ast-finetuned-audioset-10-10-0.4593
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: ast-finetuned-audioset-10-10-0.4593-finetuned-AST
results: []
ast-finetuned-audioset-10-10-0.4593-finetuned-AST
This model is a fine-tuned version of MIT/ast-finetuned-audioset-10-10-0.4593 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3787
- Accuracy: 0.9463
- F1: 0.9426
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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.7914 | 1.0 | 1467 | 0.5058 | 0.8788 | 0.8679 |
| 0.5962 | 2.0 | 2934 | 0.4318 | 0.9018 | 0.8941 |
| 0.0143 | 3.0 | 4401 | 0.4418 | 0.9233 | 0.9183 |
| 0.0002 | 4.0 | 5868 | 0.3996 | 0.9387 | 0.9342 |
| 0.0001 | 5.0 | 7335 | 0.3787 | 0.9463 | 0.9426 |
Framework versions
- Transformers 4.31.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3