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---
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 Hanhpt23/MultiMed dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7193
- Wer: 19.9744
- Cer: 14.0186
## 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: 4
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
| 0.6396 | 1.0 | 4626 | 0.7132 | 31.7615 | 22.7290 |
| 0.3406 | 2.0 | 9252 | 0.6568 | 25.4179 | 18.0443 |
| 0.1281 | 3.0 | 13878 | 0.6780 | 22.2623 | 15.5534 |
| 0.026 | 4.0 | 18504 | 0.7193 | 19.9744 | 14.0186 |
### Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.19.1
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