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language:
- zh
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- formospeech/tat_asr_aligned
model-index:
- name: Whisper Tiny Taiwanese Android
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Whisper Tiny Taiwanese Android
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the TAT ASR Aligned dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6536
- Cer: 10.3016
## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1362
- training_steps: 13620
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|:-------------:|:-------:|:-----:|:---------------:|:-------:|
| 0.371 | 0.9985 | 681 | 0.4334 | 14.4492 |
| 0.2637 | 1.9971 | 1362 | 0.3950 | 13.0672 |
| 0.1725 | 2.9956 | 2043 | 0.3962 | 12.1858 |
| 0.1102 | 3.9941 | 2724 | 0.4102 | 11.8710 |
| 0.0715 | 4.9927 | 3405 | 0.4442 | 11.9113 |
| 0.0467 | 5.9912 | 4086 | 0.4830 | 12.2436 |
| 0.0322 | 6.9897 | 4767 | 0.5100 | 11.6466 |
| 0.0234 | 7.9883 | 5448 | 0.5315 | 11.5878 |
| 0.0182 | 8.9868 | 6129 | 0.5542 | 11.8786 |
| 0.012 | 9.9853 | 6810 | 0.5834 | 11.5762 |
| 0.0083 | 10.9839 | 7491 | 0.5833 | 11.4945 |
| 0.0061 | 11.9824 | 8172 | 0.6000 | 11.1774 |
| 0.0045 | 12.9809 | 8853 | 0.6136 | 11.0700 |
| 0.0027 | 13.9795 | 9534 | 0.6144 | 10.8808 |
| 0.0008 | 14.9780 | 10215 | 0.6320 | 10.6295 |
| 0.0006 | 15.9765 | 10896 | 0.6380 | 10.6150 |
| 0.0003 | 16.9751 | 11577 | 0.6385 | 10.4755 |
| 0.0003 | 17.9736 | 12258 | 0.6498 | 10.4047 |
| 0.0001 | 18.9721 | 12939 | 0.6537 | 10.3546 |
| 0.0001 | 19.9707 | 13620 | 0.6536 | 10.3016 |
### Framework versions
- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
|