whisper-medium-engmed-v2 – AI Model by Hanhpt23 | AlphaNeural AI

You can deploy this model and start earning money today!

Hanhpt23/
whisper-medium-engmed-v2

like

0

automatic-speech-recognition

generated_from_trainer

openai/whisper-medium

endpoints_compatible

Views

No views yet

openai/whisper-medium

This model is a fine-tuned version of openai/whisper-medium on the pphuc25/EngMed dataset. It achieves the following results on the evaluation set:

Loss: 1.3051
Wer: 19.0281

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
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 100
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.8152	1.0	2268	0.7891	34.2392
0.4587	2.0	4536	0.7773	24.6287
0.3061	3.0	6804	0.8282	23.0274
0.2015	4.0	9072	0.8892	22.5628
0.1347	5.0	11340	0.9453	19.5775
0.0886	6.0	13608	1.0157	20.1560
0.0726	7.0	15876	1.0550	19.8638
0.0563	8.0	18144	1.0648	19.7586
0.0421	9.0	20412	1.0888	21.6560
0.0222	10.0	22680	1.1299	20.5330
0.0313	11.0	24948	1.1475	19.1314
0.0168	12.0	27216	1.1656	19.4918
0.0212	13.0	29484	1.1961	19.7869
0.0093	14.0	31752	1.2353	19.5599
0.0036	15.0	34020	1.2368	20.1463
0.0026	16.0	36288	1.2582	19.0077
0.0034	17.0	38556	1.2643	19.4324
0.0012	18.0	40824	1.2775	19.5064
0.0002	19.0	43092	1.2977	19.3009
0.0008	20.0	45360	1.3051	19.0281

Framework versions

Transformers 4.41.1
Pytorch 2.3.0
Datasets 2.19.1
Tokenizers 0.19.1