Whisper Small en - pbl4

This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:

• eval_loss: 0.3805
• eval_wer: 10.6595
• eval_runtime: 58.6535
• eval_samples_per_second: 2.557
• eval_steps_per_second: 0.324
• epoch: 227.2727
• step: 5000

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

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: 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: 6000
• mixed_precision_training: Native AMP

Framework versions

• Transformers 4.47.1
• Pytorch 2.4.0
• Datasets 3.2.0
• Tokenizers 0.21.0