metadata

license: bsd-3-clause
base_model: MIT/ast-finetuned-audioset-10-10-0.4593
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - wer
model-index:
  - name: ast-finetuned-audioset-10-10-0.4593-keyword_spotting2
    results: []

ast-finetuned-audioset-10-10-0.4593-keyword_spotting2

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: 1.0123
Accuracy: 0.8228
Wer: 0.1772

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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Wer
0.0008	1.0	28	1.3229	0.8228	0.1772
0.3356	2.0	56	1.3607	0.8228	0.1772
0.0035	3.0	84	1.0123	0.8228	0.1772
0.0051	4.0	112	1.5980	0.8228	0.1772
0.0001	5.0	140	1.4630	0.8228	0.1772

Framework versions

Transformers 4.35.0
Pytorch 2.1.0+cu121
Datasets 2.14.7.dev0
Tokenizers 0.14.1