Brian42521/whisper-small-hi-exp

Whisper Small Hindi Experimental

This model is a fine-tuned version of openai/whisper-small on the Common Voice 22.0 dataset. It achieves the following results on the evaluation set:

• Loss: 0.3003
• Wer: 37.3543

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: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 50
• training_steps: 500
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.3310	0.2110	100	0.4101	45.7002
0.2631	0.4219	200	0.3488	40.9286
0.2371	0.6329	300	0.3252	39.1379
0.2116	0.8439	400	0.3058	38.1371
0.1573	1.0549	500	0.3003	37.3543

Framework versions

• Transformers 5.0.0
• Pytorch 2.10.0+cu128
• Datasets 3.6.0
• Tokenizers 0.22.2