muneebharoon/whisper-small-ks

Whisper Small ks - Muneeb Haroon

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

• Loss: 1.1578
• Wer: 39.8077

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: 2
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 8
• optimizer: Use OptimizerNames.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: 10000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0123	21.2811	1000	0.9382	48.125
0.0051	42.5622	2000	0.9946	42.4519
0.0032	63.8432	3000	1.0278	41.3942
0.0	85.1081	4000	1.1138	40.5288
0.0	106.3892	5000	1.1578	39.8077
0.0	127.6703	6000	1.1869	39.8077
0.0	148.9514	7000	1.2211	40.0
0.0	170.2162	8000	1.2430	40.2404
0.0	191.4973	9000	1.2679	40.2885
0.0	212.7784	10000	1.2762	40.3365

Framework versions

• Transformers 4.49.0
• Pytorch 2.5.1+cu124
• Datasets 3.2.0
• Tokenizers 0.21.0