jethrowang/vanilla-whisper-medium_evaluated_on_iOS
05
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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: 0.0216
- eval_cer: 0.7744
- eval_runtime: 2129.3072
- evalsamplesper_second: 2.141
- evalstepsper_second: 0.134
- 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
- trainbatchsize: 32
- evalbatchsize: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lrschedulertype: linear
- lrschedulerwarmup_steps: 1521
- training_steps: 15215
- mixedprecisiontraining: Native AMP
Framework versions
- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1