March23 – AI Model by Roshana | AlphaNeural AI

You can deploy this model and start earning money today!

Roshana/
March23

like

0

automatic-speech-recognition

generated_from_trainer

endpoints_compatible

Views

No views yet

CV11_finetuning1

This model is a fine-tuned version of Roshana/Wav2Vec1_CV on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.7162
Wer: 0.3625

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: 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: 500
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.5067	0.86	400	0.6193	0.4492
0.4448	1.72	800	0.6325	0.4384
0.3781	2.59	1200	0.6248	0.4197
0.3172	3.45	1600	0.6408	0.4343
0.2556	4.31	2000	0.6593	0.4230
0.2148	5.17	2400	0.6742	0.3987
0.1779	6.03	2800	0.6658	0.3929
0.1446	6.9	3200	0.6768	0.3846
0.1248	7.76	3600	0.6809	0.3804
0.108	8.62	4000	0.7214	0.3683
0.0938	9.48	4400	0.7162	0.3625

Framework versions

Transformers 4.22.2
Pytorch 1.12.1+cu113
Datasets 2.5.1
Tokenizers 0.12.1