This model is a fine-tuned version of openai/whisper-medium on the Common Voice 16.1 + Romanian speech synthesis dataset. It achieves the following results on the evaluation set:

Loss: 0.0758
Wer: 6.0355

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: 10
eval_batch_size: 10
seed: 42
distributed_type: multi-GPU
num_devices: 3
total_train_batch_size: 30
total_eval_batch_size: 30
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 600
training_steps: 6000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.7452	0.22	250	0.6060	16.6525
0.1399	0.43	500	0.1351	13.3305
0.1444	0.65	750	0.1168	11.9676
0.1259	0.86	1000	0.1078	11.8277
0.0636	1.08	1250	0.0948	9.8382
0.0704	1.3	1500	0.0905	9.5461
0.0633	1.51	1750	0.0898	9.9385
0.0611	1.73	2000	0.0833	8.8464
0.0516	1.94	2250	0.0797	8.5757
0.0259	2.16	2500	0.0783	7.8517
0.0204	2.38	2750	0.0806	8.0646
0.024	2.59	3000	0.0775	7.6783
0.0203	2.81	3250	0.0767	7.4379
0.0129	3.03	3500	0.0761	7.1824
0.0109	3.24	3750	0.0790	7.4075
0.0096	3.46	4000	0.0768	7.3223
0.0104	3.67	4250	0.0766	6.9330
0.0101	3.89	4500	0.0722	6.3945
0.0045	4.11	4750	0.0770	6.3641
0.0052	4.32	5000	0.0763	6.3397
0.0051	4.54	5250	0.0761	6.2272
0.0038	4.75	5500	0.0756	6.1420
0.0036	4.97	5750	0.0751	6.0629
0.0025	5.19	6000	0.0758	6.0355

Framework versions

Transformers 4.37.2
Pytorch 2.2.0
Datasets 2.17.0
Tokenizers 0.15.1

VladS159/Whisper_medium_ro_VladS_6000_steps_multi_gpu_29_02_2024

Whisper Medium Ro - Sarbu Vlad - multi gpu - 3

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

VladS159/
Whisper_medium_ro_VladS_6000_steps_multi_gpu_29_02_2024