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

Loss: 1.4807
Wer: 50.5448

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: 3e-07
train_batch_size: 32
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 10
training_steps: 1200
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0334	14.29	100	1.0348	50.0908
0.0021	28.57	200	1.1971	49.4855
0.0007	42.86	300	1.2651	49.7352
0.0006	57.14	400	1.3084	49.9697
0.0005	71.43	500	1.3479	50.0605
0.0004	85.71	600	1.3835	50.3027
0.0004	100.0	700	1.4139	50.4540
0.0004	114.29	800	1.4382	50.4616
0.0004	128.57	900	1.4545	50.5297
0.0003	142.86	1000	1.4603	50.5675
0.0003	157.14	1100	1.4750	50.5599
0.0003	171.43	1200	1.4807	50.5448

Framework versions

Transformers 4.26.0.dev0
Pytorch 1.13.0+cu117
Datasets 2.7.1.dev0
Tokenizers 0.13.2

ihanif/whisper-medium-pashto

Whisper Medium Pashto

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

ihanif/
whisper-medium-pashto