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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 Condenser
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 Condenser
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: 0.6252
- Cer: 11.4109
## 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: 681
- training_steps: 6810
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.3117 | 0.9985 | 681 | 0.4649 | 17.1248 |
| 0.1805 | 1.9971 | 1362 | 0.4360 | 13.6667 |
| 0.108 | 2.9956 | 2043 | 0.4497 | 13.4248 |
| 0.0648 | 3.9941 | 2724 | 0.4710 | 12.8500 |
| 0.0349 | 4.9927 | 3405 | 0.5276 | 12.7592 |
| 0.0192 | 5.9912 | 4086 | 0.5607 | 12.4186 |
| 0.0089 | 6.9897 | 4767 | 0.5911 | 12.1183 |
| 0.0035 | 7.9883 | 5448 | 0.6032 | 11.6608 |
| 0.0009 | 8.9868 | 6129 | 0.6198 | 11.5311 |
| 0.0005 | 9.9853 | 6810 | 0.6252 | 11.4109 |
### Framework versions
- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
|