nrlt/whisper-small-mn-last2

Whisper Small - Mongolian LoRA

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

• Loss: 0.2533
• Wer: 0.1907

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 1e-4
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 32
• 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: 500
• training_steps: 4000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
1.3506	1.6892	500	0.3970	0.3962
0.7855	3.3784	1000	0.2958	0.3157
0.5229	5.0676	1500	0.2583	0.2628
0.2567	6.7568	2000	0.2361	0.2334
0.0620	8.4459	2500	0.2421	0.2158
0.0136	10.1351	3000	0.2488	0.1944
0.0348	11.8243	3500	0.2580	0.2053
0.0058	13.5135	4000	0.2533	0.1907

Framework versions

• PEFT 0.18.1
• Transformers 5.0.0
• Pytorch 2.10.0+cu128
• Datasets 4.8.3
• Tokenizers 0.22.2