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

Loss: 0.5925
Wer: 17.9209

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
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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
0.0014	20.0	1000	0.5083	17.6574
0.0008	40.0	2000	0.5600	18.1552
0.0002	60.0	3000	0.5837	17.8917
0.0002	80.0	4000	0.5925	17.9209

Framework versions

Transformers 4.43.3
Pytorch 2.4.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1

Himanshu4319/whisper-small-eng

Whisper Small eng - Himanshu

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Himanshu4319/
whisper-small-eng