whisper-large-v2-es – AI Model by Jack200133 | AlphaNeural AI

You can deploy this model and start earning money today!

Jack200133/
whisper-large-v2-es

like

0

automatic-speech-recognition

generated_from_trainer

endpoints_compatible

Views

No views yet

whisper-large-v2-es

This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.2930
Wer: 31.3542

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: 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: 200
training_steps: 6000

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0328	0.16	250	0.3149	26.25
0.0498	0.33	500	0.2925	37.9167
0.0666	0.49	750	0.2762	28.3333
0.0909	0.65	1000	0.2705	32.1875
0.0843	0.82	1250	0.2566	27.7083
0.1277	0.98	1500	0.2609	29.7917
0.0431	1.14	1750	0.2667	30.6250
0.0321	1.31	2000	0.2570	30.8333
0.0301	1.47	2250	0.2793	31.1458
0.0364	1.63	2500	0.2769	29.375
0.0303	1.8	2750	0.2755	28.6458
0.0226	1.96	3000	0.2846	27.9167
0.0185	2.12	3250	0.2863	26.9792
0.0161	2.29	3500	0.2902	27.8125
0.0165	2.45	3750	0.2903	32.7083
0.0145	2.61	4000	0.2903	29.8958
0.0123	2.78	4250	0.3076	27.8125
0.0129	2.94	4500	0.3019	28.4375
0.0145	3.1	4750	0.2917	26.5625
0.0118	3.27	5000	0.2953	33.6458
0.0099	3.43	5250	0.2881	33.0208
0.0088	3.59	5500	0.2922	31.5625
0.0118	3.76	5750	0.2935	30.5208
0.0103	3.92	6000	0.2930	31.3542

Framework versions

Transformers 4.34.0.dev0
Pytorch 1.12.1+cu116
Datasets 2.4.0
Tokenizers 0.12.1