Whisper Medium fine-tuned for Tatar language

This model is a fine-tuned version of openai/whisper-small on the Common Voice 16.1 dataset. It achieves the following results on the evaluation set:

• Loss: 0.2809
• Wer: 34.8445

Training and evaluation data

Training data was taken from Common Voice 16.1 dataset

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 1e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 16
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 250
• training_steps: 2000
• mixed_precision_training: Native AMP

Training results

Framework versions

• Transformers 4.41.0
• Pytorch 2.1.2
• Datasets 2.19.1
• Tokenizers 0.19.1