metadata

license: bsd-3-clause
base_model: MIT/ast-finetuned-audioset-10-10-0.4593
tags:
  - generated_from_trainer
datasets:
  - audiofolder
metrics:
  - f1
model-index:
  - name: ast-finetuned-audioset-10-10-0.4593-finetuned-AST
    results:
      - task:
          name: Audio Classification
          type: audio-classification
        dataset:
          name: audiofolder
          type: audiofolder
          config: Data_Train
          split: train
          args: Data_Train
        metrics:
          - name: F1
            type: f1
            value: 0.9276872550130031

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 audiofolder dataset. It achieves the following results on the evaluation set:

Loss: 0.4230
F1: 0.9277

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	F1
0.1148	1.0	1449	0.5953	0.8492
0.234	2.0	2898	0.5676	0.8704
0.2579	3.0	4347	0.4810	0.9086
0.077	4.0	5796	0.4230	0.9277
0.0001	5.0	7245	0.4369	0.9232

Framework versions

Transformers 4.31.0.dev0
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3