whisper-hindi-peft

This model is a fine-tuned version of openai/whisper-large-v3 on the common_voice_11_0 dataset. It achieves the following results on the evaluation set:

• Loss: 0.1044
• Wer: 0.2829

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: 0.0001
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 32
• 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: 100
• training_steps: 1000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.4265	1.4689	200	0.1282	0.3696
0.2581	2.9377	400	0.0941	0.2797
0.1579	4.4103	600	0.0984	0.2850
0.1285	5.8791	800	0.0999	0.2795
0.0862	7.3516	1000	0.1044	0.2829

Framework versions

• PEFT 0.14.0
• Transformers 4.48.3
• Pytorch 2.5.1+cu124
• Datasets 3.3.2
• Tokenizers 0.21.0