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---
language:
- zh
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: openai/whisper-small
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. -->
# openai/whisper-small
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the pphuc25/ChiMed dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1603
- Wer: 84.4794
- Cer: 25.0446
## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
| 0.6517 | 1.0 | 161 | 0.8312 | 272.4951 | 128.1194 |
| 0.3421 | 2.0 | 322 | 0.7985 | 171.1198 | 63.7478 |
| 0.2206 | 3.0 | 483 | 0.9271 | 152.0629 | 59.8039 |
| 0.103 | 4.0 | 644 | 1.0397 | 85.2652 | 28.4091 |
| 0.0834 | 5.0 | 805 | 1.0335 | 92.7308 | 26.6266 |
| 0.0578 | 6.0 | 966 | 1.0893 | 86.2475 | 28.6319 |
| 0.0617 | 7.0 | 1127 | 1.1243 | 88.2122 | 28.0303 |
| 0.0407 | 8.0 | 1288 | 1.1577 | 84.6758 | 28.6988 |
| 0.032 | 9.0 | 1449 | 1.1847 | 83.3006 | 26.7157 |
| 0.0223 | 10.0 | 1610 | 1.1404 | 94.1061 | 32.5980 |
| 0.0144 | 11.0 | 1771 | 1.1927 | 88.0157 | 28.3645 |
| 0.0087 | 12.0 | 1932 | 1.1309 | 88.4086 | 26.4483 |
| 0.0126 | 13.0 | 2093 | 1.1613 | 84.0864 | 25.5570 |
| 0.0047 | 14.0 | 2254 | 1.1863 | 86.4440 | 25.7353 |
| 0.0061 | 15.0 | 2415 | 1.1674 | 83.6935 | 27.0276 |
| 0.0013 | 16.0 | 2576 | 1.1762 | 83.4971 | 25.2005 |
| 0.0007 | 17.0 | 2737 | 1.1697 | 84.8723 | 25.4679 |
| 0.0006 | 18.0 | 2898 | 1.1614 | 83.8900 | 25.2897 |
| 0.0002 | 19.0 | 3059 | 1.1597 | 84.4794 | 25.0446 |
| 0.0002 | 20.0 | 3220 | 1.1603 | 84.4794 | 25.0446 |
### Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.19.1
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