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

Loss: 0.5733
Wer: 31.0300

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: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Use OptimizerNames.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: 500
training_steps: 4000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0087	12.1951	1000	0.4534	32.1961
0.0004	24.3902	2000	0.5305	31.3755
0.0001	36.5854	3000	0.5546	30.9652
0.0001	48.7805	4000	0.5733	31.0300

Framework versions

Transformers 4.49.0
Pytorch 2.5.1+cu124
Datasets 3.3.2
Tokenizers 0.21.0

Illuminati-014/whisper-medium-hi

Whisper Medium Hi - Illuminati014

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Illuminati-014/
whisper-medium-hi