whisper-base-en-atc

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

• Loss: 2.9906
• Wer: 1.7584

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: 16
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 100
• num_epochs: 1
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.5561	0.2688	250	2.9956	1.5391
0.3877	0.5376	500	2.9964	1.8011
0.3324	0.8065	750	2.9906	1.7584

Framework versions

• Transformers 5.3.0
• Pytorch 2.10.0+cu130
• Datasets 4.7.0
• Tokenizers 0.22.2