ifc0nfig/whisper-small-hi-vyapar

Whisper Small Hi - Vyapar

This model is a fine-tuned version of openai/whisper-small on the Vyapar Calling Data dataset. It achieves the following results on the evaluation set:

• Loss: 2.0664
• Wer: 62.9259

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 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
0.1183	8.7753	1000	1.5163	56.7134
0.0037	17.5463	2000	1.8823	54.8297
0.0003	26.3172	3000	2.0341	54.9499
0.0002	35.0881	4000	2.0664	62.9259

Framework versions

• Transformers 4.47.1
• Pytorch 2.5.1+cu118
• Datasets 3.2.0
• Tokenizers 0.21.0