whisper-medium-studio-records

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

• Loss: 0.0328
• Wer: 15.6258

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: 6000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0573	0.4110	1000	0.0880	42.2742
0.0351	0.8220	2000	0.0619	31.4008
0.0149	1.2330	3000	0.0463	23.6377
0.0114	1.6441	4000	0.0358	18.2384
0.0036	2.0551	5000	0.0356	16.8201
0.0035	2.4661	6000	0.0328	15.6258

Framework versions

• Transformers 4.42.2
• Pytorch 2.1.1+cu121
• Datasets 2.20.0
• Tokenizers 0.19.1