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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: 0.9626
- Wer: 102.9470
- Cer: 27.5178
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------:|
| 0.5624 | 1.0 | 161 | 0.7102 | 103.7328 | 36.8093 |
| 0.2753 | 2.0 | 322 | 0.7326 | 117.6817 | 44.2291 |
| 0.127 | 3.0 | 483 | 0.7775 | 86.0511 | 31.1720 |
| 0.0519 | 4.0 | 644 | 0.8256 | 103.5363 | 31.2834 |
| 0.0423 | 5.0 | 805 | 0.8966 | 119.4499 | 36.9207 |
| 0.0251 | 6.0 | 966 | 0.8908 | 105.8939 | 29.3449 |
| 0.0137 | 7.0 | 1127 | 0.9214 | 84.6758 | 26.2478 |
| 0.0169 | 8.0 | 1288 | 0.9114 | 87.0334 | 24.3761 |
| 0.0107 | 9.0 | 1449 | 0.9319 | 104.9116 | 28.4759 |
| 0.0025 | 10.0 | 1610 | 0.9353 | 103.5363 | 27.3173 |
| 0.0007 | 11.0 | 1771 | 0.9370 | 105.6974 | 28.9216 |
| 0.0017 | 12.0 | 1932 | 0.9412 | 103.3399 | 27.8075 |
| 0.0006 | 13.0 | 2093 | 0.9438 | 102.3576 | 27.7852 |
| 0.0003 | 14.0 | 2254 | 0.9575 | 103.5363 | 29.3449 |
| 0.0003 | 15.0 | 2415 | 0.9568 | 102.3576 | 27.8743 |
| 0.0002 | 16.0 | 2576 | 0.9591 | 103.1434 | 27.6738 |
| 0.0002 | 17.0 | 2737 | 0.9601 | 102.9470 | 27.5401 |
| 0.0002 | 18.0 | 2898 | 0.9613 | 102.7505 | 27.5178 |
| 0.0002 | 19.0 | 3059 | 0.9622 | 102.9470 | 27.5401 |
| 0.0002 | 20.0 | 3220 | 0.9626 | 102.9470 | 27.5178 |
### Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.19.1
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