whisper-small-en-VB

This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.6560
• Wer Ortho: 11.0424
• Wer: 7.8659

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: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Use 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: 50
• training_steps: 1000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Ortho	Wer
0.0373	3.9683	250	0.5479	11.1283	8.2365
0.001	7.9365	500	0.6287	11.0939	7.6638
0.0003	11.9048	750	0.6504	11.0424	7.8659
0.0003	15.8730	1000	0.6560	11.0424	7.8659

Framework versions

• Transformers 4.46.2
• Pytorch 2.4.0
• Datasets 3.1.0
• Tokenizers 0.20.0