This model is a fine-tuned version of anton-l/distilhubert-ft-keyword-spotting on the audiofolder dataset. It achieves the following results on the evaluation set:

Loss: 0.0459
Accuracy: 0.9850

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: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 128
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
0.1536	1.0	215	0.1282	0.9606
0.0809	2.0	430	0.0752	0.9763
0.0839	3.0	645	0.0638	0.9783
0.0536	4.0	861	0.0588	0.9794
0.0412	4.99	1075	0.0459	0.9850

Framework versions

Transformers 4.37.2
Pytorch 2.1.0+cu121
Datasets 2.16.1
Tokenizers 0.15.1

abhiramk6/distilhubert-ft-keyword-spotting-finetuned-ks-ob

distilhubert-ft-keyword-spotting-finetuned-ks-ob

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

abhiramk6/
distilhubert-ft-keyword-spotting-finetuned-ks-ob