This model is a fine-tuned version of openai/whisper-small on the Vyapar Calling Data 5 calls manual data dataset. It achieves the following results on the evaluation set:

Loss: 2.1062
Wer: 61.9102

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
0.0024	31.2540	1000	1.9432	71.9217
0.0001	62.5079	2000	2.0505	62.6007
0.0001	93.7619	3000	2.0913	61.6801
0.0001	125.0	4000	2.1062	61.9102

Framework versions

Transformers 4.47.1
Pytorch 2.5.1+cu118
Datasets 3.2.0
Tokenizers 0.21.0

ifc0nfig/whisper-small-hi-vyapar_v5_manual

Whisper Small Hi - Vyapar V5

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

ifc0nfig/
whisper-small-hi-vyapar_v5_manual