Eyesiga/whisper_base_en

Whisper base english

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

• Loss: 0.2710
• Wer: 7.7095

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: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 1000
• training_steps: 4000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.395	3.33	1000	0.1988	7.4860
0.0295	6.67	2000	0.2389	7.3743
0.0026	10.0	3000	0.2645	7.5978
0.0011	13.33	4000	0.2710	7.7095

Framework versions

• Transformers 4.39.0.dev0
• Pytorch 2.1.0+cu121
• Datasets 2.17.1
• Tokenizers 0.15.2