whisper-medium-finetuned

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

• eval_loss: 0.0120
• eval_wer: 28.7151
• eval_runtime: 98.274
• eval_samples_per_second: 0.407
• eval_steps_per_second: 0.407
• epoch: 9.0
• step: 540

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: 2e-05
• train_batch_size: 2
• eval_batch_size: 1
• seed: 42
• optimizer: Use OptimizerNames.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: 30
• num_epochs: 10

Framework versions

• Transformers 4.48.0
• Pytorch 2.9.0+cu128
• Datasets 4.4.1
• Tokenizers 0.21.4