wav2vec2-base-finetuned-stop-classification-1 – AI Model by suyuanliu | AlphaNeural AI

You can deploy this model and start earning money today!

suyuanliu/
wav2vec2-base-finetuned-stop-classification-1

like

0

audio-classification

generated_from_trainer

endpoints_compatible

Views

No views yet

wav2vec2-base-finetuned-stop-classification-1

This model is a fine-tuned version of facebook/wav2vec2-base on the audiofolder dataset. It achieves the following results on the evaluation set:

Loss: 0.2121
Accuracy: 0.9285

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: 64
eval_batch_size: 64
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 256
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.6921	0.99	18	0.6781	0.6185
0.612	1.97	36	0.5797	0.7207
0.5046	2.96	54	0.3820	0.8569
0.3956	4.0	73	0.2827	0.9012
0.3428	4.99	91	0.2915	0.8903
0.3222	5.97	109	0.2333	0.9162
0.3033	6.96	127	0.2403	0.9162
0.2743	8.0	146	0.2129	0.9237
0.2494	8.99	164	0.2121	0.9285
0.2543	9.86	180	0.2199	0.9251

Framework versions

Transformers 4.27.4
Pytorch 1.13.0
Datasets 2.7.1
Tokenizers 0.13.2