wav2vec2-finetuned-on-shEMO – AI Model by minoosh | AlphaNeural AI

You can deploy this model and start earning money today!

minoosh/
wav2vec2-finetuned-on-shEMO

like

0

audio-classification

generated_from_trainer

endpoints_compatible

Views

No views yet

wav2vec2-finetuned-on-shEMO

This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 1.0218
Accuracy: 0.8

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
gradient_accumulation_steps: 4
total_train_batch_size: 32
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

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.4581	1.0	75	1.4405	0.5767
1.0505	2.0	150	0.9797	0.71
0.9486	3.0	225	0.8445	0.74
0.7795	4.0	300	0.9015	0.6867
0.6058	5.0	375	0.7416	0.7767
0.5169	6.0	450	0.7565	0.78
0.4251	7.0	525	0.6422	0.82
0.3567	8.0	600	0.5284	0.8367
0.2806	9.0	675	0.6506	0.8033
0.2108	10.0	750	0.6477	0.8333
0.1468	11.0	825	0.5919	0.85
0.1624	12.0	900	0.6010	0.8533
0.1021	13.0	975	0.6798	0.8533
0.0647	14.0	1050	0.7265	0.8567
0.0502	15.0	1125	0.6910	0.8667
0.0326	16.0	1200	0.7374	0.8667
0.0554	17.0	1275	0.7250	0.8567
0.0312	18.0	1350	0.7943	0.8567
0.0729	19.0	1425	0.7315	0.86
0.0562	20.0	1500	0.7602	0.8533

Framework versions

Transformers 4.28.1
Pytorch 2.0.0+cu118
Datasets 2.11.0
Tokenizers 0.13.3