large_config – AI Model by huydt | AlphaNeural AI

You can deploy this model and start earning money today!

huydt/
large_config

like

0

automatic-speech-recognition

generated_from_trainer

endpoints_compatible

Views

No views yet

large_config

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

Loss: 0.2441
Wer: 17.8570
Cer: 8.0073

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: 1e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 10000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer
0.5155	0.1	1000	0.4045	27.7845	12.1308
0.5436	1.02	2000	0.3784	27.0983	11.9181
0.265	1.12	3000	0.3227	22.8815	10.0236
0.4765	2.04	4000	0.3021	21.9744	9.6005
0.1818	2.14	5000	0.3002	21.0336	9.1830
0.4031	3.05	6000	0.2496	18.0914	7.9181
0.1991	3.15	7000	0.2971	21.7029	9.9984
0.3023	4.07	8000	0.2445	17.7946	7.9248
0.2185	4.17	9000	0.2842	20.3760	9.2891
0.2114	5.09	10000	0.2441	17.8570	8.0073

Framework versions

Transformers 4.26.1
Pytorch 1.13.1+cu117
Datasets 2.9.0
Tokenizers 0.13.2