whisper-medium-toi

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

• Loss: 2.8215
• Wer: 59.6163

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: 4
• eval_batch_size: 4
• 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: 4000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.4727	1.47	500	2.0656	70.8002
0.2033	2.95	1000	2.0971	67.6416
0.0658	4.42	1500	2.3894	62.0262
0.0281	5.9	2000	2.5443	62.2134
0.0104	7.37	2500	2.6873	61.8390
0.0046	8.85	3000	2.7252	60.6458
0.0004	10.32	3500	2.7891	60.8563
0.0003	11.8	4000	2.8215	59.6163

Framework versions

• Transformers 4.26.0.dev0
• Pytorch 1.12.1+cu113
• Datasets 2.7.1
• Tokenizers 0.13.2