jethrowang/vanilla-whisper-medium_evaluated_on_PCmic

Whisper Medium Hakka Condenser

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

• eval_loss: 0.0196
• eval_cer: 0.6577
• eval_runtime: 2073.9271
• eval_samples_per_second: 2.198
• eval_steps_per_second: 0.137
• step: 0

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: 32
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 1521
• training_steps: 15215
• mixed_precision_training: Native AMP

Framework versions

• Transformers 4.42.3
• Pytorch 2.3.0+cu121
• Datasets 2.20.0
• Tokenizers 0.19.1