This model is a fine-tuned version of openai/whisper-large-v2 on the Common Voice 14.0 dataset. It achieves the following results on the evaluation set:

Loss: 0.5744
Wer: 34.2870

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: 32
eval_batch_size: 16
seed: 42
distributed_type: multi-GPU
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: 500
training_steps: 1000

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0134	9.07	1000	0.5744	34.2870

Framework versions

Transformers 4.37.0.dev0
Pytorch 2.1.0+cu121
Datasets 2.16.2.dev0
Tokenizers 0.15.0

lanmandragoran/urdu-whisper-large-v2-zero-stage-2-bf16

Whisper Large Ur

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

lanmandragoran/
urdu-whisper-large-v2-zero-stage-2-bf16