Whisper Tiny Hakka Condenser
This model is a fine-tuned version of openai/whisper-tiny on the HAT ASR Aligned dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.0505
- eval_cer: 2.4343
- eval_runtime: 597.3234
- eval_samples_per_second: 7.632
- eval_steps_per_second: 0.239
- 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: 64
- eval_batch_size: 32
- 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: 15210
- mixed_precision_training: Native AMP
Framework versions
- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for jethrowang/vanilla-whisper-tiny_evaluated_on_condenser
Base model
openai/whisper-tiny