wav2vec2-base_toy_train_data_augmented – AI Model by scasutt | AlphaNeural AI

You can deploy this model and start earning money today!

scasutt/
wav2vec2-base_toy_train_data_augmented

like

0

automatic-speech-recognition

generated_from_trainer

endpoints_compatible

Views

No views yet

wav2vec2-base_toy_train_data_augmented

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: 1.0238
Wer: 0.6969

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: 0.0001
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 1000
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
3.12	1.05	250	3.3998	0.9982
3.0727	2.1	500	3.1261	0.9982
1.9729	3.15	750	1.4868	0.9464
1.3213	4.2	1000	1.2598	0.8833
1.0508	5.25	1250	1.0014	0.8102
0.8483	6.3	1500	0.9475	0.7944
0.7192	7.35	1750	0.9493	0.7686
0.6447	8.4	2000	0.9872	0.7573
0.6064	9.45	2250	0.9587	0.7447
0.5384	10.5	2500	0.9332	0.7320
0.4985	11.55	2750	0.9926	0.7315
0.4643	12.6	3000	1.0008	0.7292
0.4565	13.65	3250	0.9522	0.7171
0.449	14.7	3500	0.9685	0.7140
0.4307	15.75	3750	1.0080	0.7077
0.4239	16.81	4000	0.9950	0.7023
0.389	17.86	4250	1.0260	0.7007
0.3471	18.91	4500	1.0012	0.6966
0.3276	19.96	4750	1.0238	0.6969

Framework versions

Transformers 4.17.0
Pytorch 1.11.0+cu102
Datasets 2.0.0
Tokenizers 0.11.6