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language:
- en
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: openai/whisper-tiny
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-tiny
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Hanhpt23/SilvarMed dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1653
- Wer: 2.6729
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.0595 | 1.0 | 2438 | 0.1336 | 4.7314 |
| 0.0301 | 2.0 | 4876 | 0.1503 | 5.6790 |
| 0.0202 | 3.0 | 7314 | 0.1391 | 5.3653 |
| 0.0181 | 4.0 | 9752 | 0.1544 | 6.9011 |
| 0.0155 | 5.0 | 12190 | 0.1623 | 4.4047 |
| 0.0067 | 6.0 | 14628 | 0.1711 | 4.1890 |
| 0.0075 | 7.0 | 17066 | 0.1636 | 3.7577 |
| 0.0073 | 8.0 | 19504 | 0.1676 | 3.2218 |
| 0.005 | 9.0 | 21942 | 0.1756 | 3.5616 |
| 0.0003 | 10.0 | 24380 | 0.1668 | 3.2675 |
| 0.0023 | 11.0 | 26818 | 0.1702 | 3.2741 |
| 0.0025 | 12.0 | 29256 | 0.1662 | 3.0257 |
| 0.0002 | 13.0 | 31694 | 0.1692 | 2.9996 |
| 0.0 | 14.0 | 34132 | 0.1755 | 4.4569 |
| 0.0008 | 15.0 | 36570 | 0.1713 | 3.0192 |
| 0.0001 | 16.0 | 39008 | 0.1620 | 2.7839 |
| 0.0 | 17.0 | 41446 | 0.1718 | 2.7317 |
| 0.0 | 18.0 | 43884 | 0.1659 | 2.7970 |
| 0.0 | 19.0 | 46322 | 0.1653 | 2.6925 |
| 0.0 | 20.0 | 48760 | 0.1653 | 2.6729 |
### Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0
- Datasets 3.2.0
- Tokenizers 0.19.1
|