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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 Simulated 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 Simulated 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: 0.7397
- Cer: 11.2806
## 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 |
|:-------------:|:-------:|:-----:|:---------------:|:-------:|
| 0.3641 | 0.9985 | 681 | 0.4668 | 19.0185 |
| 0.2569 | 1.9971 | 1362 | 0.4366 | 14.5059 |
| 0.1682 | 2.9956 | 2043 | 0.4342 | 13.5919 |
| 0.1095 | 3.9941 | 2724 | 0.4588 | 13.0167 |
| 0.0693 | 4.9927 | 3405 | 0.4854 | 12.6401 |
| 0.0455 | 5.9912 | 4086 | 0.5303 | 13.1776 |
| 0.0323 | 6.9897 | 4767 | 0.5626 | 12.8424 |
| 0.0228 | 7.9883 | 5448 | 0.5940 | 12.4495 |
| 0.0168 | 8.9868 | 6129 | 0.6214 | 12.4219 |
| 0.0124 | 9.9853 | 6810 | 0.6661 | 13.1648 |
| 0.0091 | 10.9839 | 7491 | 0.6534 | 12.1909 |
| 0.0067 | 11.9824 | 8172 | 0.6671 | 12.1441 |
| 0.0036 | 12.9809 | 8853 | 0.6948 | 12.0141 |
| 0.0016 | 13.9795 | 9534 | 0.6962 | 11.7995 |
| 0.0011 | 14.9780 | 10215 | 0.7180 | 11.6767 |
| 0.0008 | 15.9765 | 10896 | 0.7170 | 11.5896 |
| 0.0005 | 16.9751 | 11577 | 0.7260 | 11.5133 |
| 0.0002 | 17.9736 | 12258 | 0.7299 | 11.3793 |
| 0.0002 | 18.9721 | 12939 | 0.7373 | 11.2399 |
| 0.0001 | 19.9707 | 13620 | 0.7397 | 11.2806 |
### Framework versions
- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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