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: 0.5159
- eval_model_preparation_time: 0.0024
- eval_cer: 8.4391
- eval_runtime: 1490.3693
- eval_samples_per_second: 3.768
- eval_steps_per_second: 0.118
- 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
- train_batch_size: 64
- eval_batch_size: 32
- 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: 681
- training_steps: 6810
- mixed_precision_training: Native AMP
Framework versions
- Transformers 4.49.0
- Pytorch 2.0.0.post304
- Datasets 3.3.2
- Tokenizers 0.21.0
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Model tree for jethrowang/whisper-tiny_tat_vanilla_evaluated_on_lavalier
Base model
openai/whisper-tiny