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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: 0.7176
- Wer: 20.2138
- Cer: 14.0973
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
| 0.5854 | 1.0 | 4626 | 0.7068 | 33.7558 | 24.6972 |
| 0.3884 | 2.0 | 9252 | 0.6462 | 26.2113 | 19.0993 |
| 0.119 | 3.0 | 13878 | 0.6747 | 21.5288 | 15.1996 |
| 0.0365 | 4.0 | 18504 | 0.7176 | 20.2138 | 14.0973 |
### Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.19.1
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