jethrowang/whisper-tiny_tat_vanilla_evaluated_on_ios
03
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Whisper Tiny Taiwanese Condenser
This model is a fine-tuned version of openai/whisper-tiny on the TAT ASR Aligned dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.5666
- evalmodelpreparation_time: 0.0031
- eval_cer: 9.7925
- eval_runtime: 1465.3494
- evalsamplesper_second: 3.833
- evalstepsper_second: 0.12
- 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: 0.0001
- trainbatchsize: 64
- evalbatchsize: 32
- seed: 42
- optimizer: Use adamwtorch with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
- lrschedulertype: linear
- lrschedulerwarmup_steps: 681
- training_steps: 6810
- mixedprecisiontraining: Native AMP
Framework versions
- Transformers 4.49.0
- Pytorch 2.0.0.post304
- Datasets 3.3.2
- Tokenizers 0.21.0