whisper-small-me

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

Model description

More information needed

More information needed

More information needed

The following hyperparameters were used during training:

learning_rate: 1e-05
train_batch_size: 128
eval_batch_size: 128
seed: 42
distributed_type: multi-GPU
num_devices: 2
total_train_batch_size: 256
total_eval_batch_size: 256
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 100
num_epochs: 5.0
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Mazanderani Wer	Mazanderani Cer	Gilaki Wer	Gilaki Cer	Zazaki Wer	Zazaki Cer	Laki Kurdish Wer	Laki Kurdish Cer	Talysh Wer	Talysh Cer	Hawrami Wer	Hawrami Cer	Southern Kurdish Wer	Southern Kurdish Cer	Avg Wer	Avg Cer
0.6946	1.0	82	0.7662	0.8120	0.3224	0.9556	0.3751	1.0270	1.0389	0.7939	0.2733	0.9167	0.3333	0.5246	0.1155	0.6801	0.2192	0.8157	0.3825
0.3864	2.0	164	0.5172	0.6093	0.1846	0.9579	0.3454	0.7451	0.2813	0.5644	0.1547	1.0	0.5	0.3806	0.0773	0.5484	0.1743	0.6865	0.2454
0.3234	3.0	246	0.4686	0.5476	0.1652	0.9633	0.3514	0.6740	0.2363	0.5231	0.1362	1.0	0.5	0.3533	0.0722	0.4936	0.1674	0.6507	0.2327
0.2786	4.0	328	0.4527	0.5278	0.1596	0.9083	0.3179	0.6422	0.2133	0.5047	0.1334	1.0	0.5	0.3485	0.0732	0.4948	0.1769	0.6323	0.2249
0.2586	5.0	410	0.4509	0.5278	0.1615	0.9176	0.3175	0.6324	0.2020	0.4904	0.1247	1.0	0.5	0.3459	0.0708	0.4930	0.1718	0.6296	0.2212