This model is a fine-tuned version of openai/whisper-medium on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:

Loss: 0.3857
Wer: 34.2123

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: 16
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: 500
training_steps: 8000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.4593	1.2330	1000	0.2504	42.2983
0.1318	2.4661	2000	0.2344	37.8429
0.0625	3.6991	3000	0.2582	35.9282
0.0274	4.9322	4000	0.2927	36.6139
0.009	6.1652	5000	0.3429	35.1365
0.0029	7.3983	6000	0.3625	34.7588
0.0008	8.6313	7000	0.3815	34.4740
0.0003	9.8644	8000	0.3857	34.2123

Framework versions

Transformers 4.42.0.dev0
Pytorch 2.3.1+cu118
Datasets 2.20.0
Tokenizers 0.19.1

roshna-omer/whisper-mid-ku-ckb-fa

Whisper Small Kurdish - Sorani

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

roshna-omer/
whisper-mid-ku-ckb-fa