Jpep26/repo_name1

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: 0.6020
• Cer: 0.4962
• Wer: 0.4877
• Mean: 0.4919

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: 32
• eval_batch_size: 16
• 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
2.3893	0.3817	50	2.0607	0.4421	0.7020	0.5720
1.2402	0.7634	100	1.0999	0.3408	0.5773	0.4591
0.7512	1.1450	150	0.7303	0.7268	0.5418	0.6343
0.593	1.5267	200	0.6020	0.4962	0.4877	0.4919

Framework versions

• Transformers 4.44.2
• Pytorch 2.0.1+cu117
• Datasets 2.18.0
• Tokenizers 0.19.1