metadata
language:
- zh
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- formospeech/hat_asr_aligned
model-index:
- name: Whisper Tiny Hakka Condenser
results: []
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:
- Loss: 0.0945
- Cer: 4.1693
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: 488
- training_steps: 4880
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|---|---|---|---|---|
| 0.5588 | 0.9980 | 488 | 0.5489 | 24.8653 |
| 0.1837 | 1.9959 | 976 | 0.1979 | 8.1316 |
| 0.109 | 2.9939 | 1464 | 0.1409 | 5.4419 |
| 0.0765 | 3.9918 | 1952 | 0.1202 | 4.8720 |
| 0.0524 | 4.9898 | 2440 | 0.1075 | 4.2675 |
| 0.0391 | 5.9877 | 2928 | 0.1009 | 4.2479 |
| 0.0272 | 6.9857 | 3416 | 0.0984 | 4.4629 |
| 0.0232 | 7.9836 | 3904 | 0.0954 | 4.0791 |
| 0.0196 | 8.9816 | 4392 | 0.0948 | 3.9046 |
| 0.015 | 9.9796 | 4880 | 0.0945 | 4.1693 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1