whisper-small-hi42

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

• eval_loss: 3.3630
• eval_wer: 894.1176
• eval_runtime: 6743.3326
• eval_samples_per_second: 0.938
• eval_steps_per_second: 0.234
• epoch: 0.3687
• step: 2500

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: 3e-05
• train_batch_size: 4
• eval_batch_size: 4
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 8
• optimizer: Use adamw_torch 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: 500
• training_steps: 5000

Framework versions

• Transformers 4.47.0
• Pytorch 2.5.1+cu121
• Datasets 3.3.1
• Tokenizers 0.21.0