whisper-es-pr-pe-lora-v7

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

• Loss: 0.1256
• Wer: 0.0780

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: 5e-05
• train_batch_size: 4
• eval_batch_size: 4
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 8
• 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: 200
• training_steps: 1200
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
1.475	0.3333	400	3.8148	2.4353
0.1218	1.0983	800	0.1386	0.0817
0.0974	1.4317	1200	0.1256	0.0780

Framework versions

• PEFT 0.18.0
• Transformers 4.57.2
• Pytorch 2.9.0+cu126
• Datasets 4.4.1
• Tokenizers 0.22.1