metadata

tags:
  - audio-classification
  - generated_from_trainer
datasets:
  - superb
metrics:
  - accuracy
base_model: vumichien/nonsemantic-speech-trillsson3
model-index:
  - name: trillsson3-ft-keyword-spotting-11
    results: []

trillsson3-ft-keyword-spotting-11

This model is a fine-tuned version of vumichien/nonsemantic-speech-trillsson3 on the superb dataset. It achieves the following results on the evaluation set:

Loss: 0.3166
Accuracy: 0.9088

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: 0.0003
train_batch_size: 32
eval_batch_size: 32
seed: 0
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: 20.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
2.9219	1.0	399	1.2023	0.6217
0.9604	2.0	798	0.5437	0.8117
0.7608	3.0	1197	0.4222	0.8888
0.7045	4.0	1596	0.3881	0.8932
0.659	5.0	1995	0.3706	0.8847
0.6541	6.0	2394	0.3553	0.8917
0.6448	7.0	2793	0.3482	0.8953
0.6288	8.0	3192	0.3409	0.8989
0.641	9.0	3591	0.3297	0.9051
0.6369	10.0	3990	0.3325	0.9042
0.6218	11.0	4389	0.3250	0.9064
0.6247	12.0	4788	0.3312	0.8959
0.6284	13.0	5187	0.3217	0.9069
0.6213	14.0	5586	0.3301	0.8978
0.6274	15.0	5985	0.3180	0.9081
0.627	16.0	6384	0.3257	0.9020
0.6227	17.0	6783	0.3193	0.9056
0.6192	18.0	7182	0.3199	0.9066
0.6075	19.0	7581	0.3183	0.9073
0.6196	20.0	7980	0.3166	0.9088

Framework versions

Transformers 4.23.0.dev0
Pytorch 1.12.1+cu113
Datasets 2.6.1
Tokenizers 0.13.1