---
language:
- de
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: openai/whisper-base
  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-base

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Hanhpt23/GermanMed-full dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8154
- Wer: 28.0469

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.694         | 1.0   | 194  | 0.6826          | 38.7329 |
| 0.3399        | 2.0   | 388  | 0.6960          | 39.2780 |
| 0.1866        | 3.0   | 582  | 0.7193          | 42.8057 |
| 0.1157        | 4.0   | 776  | 0.7415          | 31.9963 |
| 0.0853        | 5.0   | 970  | 0.7792          | 32.7265 |
| 0.0574        | 6.0   | 1164 | 0.7686          | 33.7036 |
| 0.0358        | 7.0   | 1358 | 0.7852          | 33.1791 |
| 0.0423        | 8.0   | 1552 | 0.8025          | 32.1917 |
| 0.027         | 9.0   | 1746 | 0.8138          | 31.2044 |
| 0.0172        | 10.0  | 1940 | 0.8155          | 29.0548 |
| 0.0182        | 11.0  | 2134 | 0.8280          | 30.7004 |
| 0.0053        | 12.0  | 2328 | 0.8268          | 30.4227 |
| 0.0066        | 13.0  | 2522 | 0.8221          | 30.0319 |
| 0.0023        | 14.0  | 2716 | 0.8166          | 29.5176 |
| 0.0007        | 15.0  | 2910 | 0.8215          | 28.6948 |
| 0.0012        | 16.0  | 3104 | 0.8262          | 28.4789 |
| 0.0003        | 17.0  | 3298 | 0.8158          | 28.3143 |
| 0.0004        | 18.0  | 3492 | 0.8154          | 27.9338 |
| 0.0003        | 19.0  | 3686 | 0.8154          | 27.9646 |
| 0.0003        | 20.0  | 3880 | 0.8154          | 28.0469 |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.19.1