nicolarsen/whisper-medium-2-F

Whisper da-nst

This model is a fine-tuned version of openai/whisper-medium on the common_voice_14_0 dataset. It achieves the following results on the evaluation set:

• Loss: 0.7234
• Wer: 35.3094

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: 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: 500
• training_steps: 5000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0133	4.04	1000	0.6362	48.9279
0.0025	9.04	2000	0.6635	37.4731
0.0001	14.03	3000	0.6959	34.1296
0.0001	19.03	4000	0.7166	35.1821
0.0	24.03	5000	0.7234	35.3094

Framework versions

• Transformers 4.37.2
• Pytorch 2.2.0+cu121
• Datasets 2.18.0
• Tokenizers 0.15.1