This model is a fine-tuned version of openai/whisper-medium on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:

eval_loss: 0.2680
eval_wer: 15.6053
eval_runtime: 3549.0061
eval_samples_per_second: 0.815
eval_steps_per_second: 0.102
epoch: 3.67
step: 500

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
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 50
training_steps: 1000
mixed_precision_training: Native AMP

Framework versions

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

shripadbhat/whisper-medium-hi

Whisper Medium Hindi

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Framework versions

shripadbhat/
whisper-medium-hi