Jpep26/repo_name

Test

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

• Loss: 0.9167
• Cer: 0.8486
• Wer: 0.7054
• Mean: 0.7770

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: 500
• training_steps: 200
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Cer	Wer	Mean
2.9457	0.6410	50	2.6739	0.5791	0.8056	0.6923
1.7821	1.2821	100	1.6827	0.4622	0.6561	0.5592
1.2153	1.9231	150	1.1411	0.4216	0.6022	0.5119
0.8636	2.5641	200	0.9167	0.8486	0.7054	0.7770

Framework versions

• Transformers 4.45.0.dev0
• Pytorch 2.1.2+cu121
• Datasets 2.20.0
• Tokenizers 0.19.1