|
|
--- |
|
|
language: |
|
|
- de |
|
|
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/GermanMed-full dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 0.7961 |
|
|
- Wer: 26.1648 |
|
|
|
|
|
## 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 | |
|
|
|:-------------:|:-----:|:----:|:---------------:|:-------:| |
|
|
| 0.6649 | 1.0 | 194 | 0.6657 | 43.7108 | |
|
|
| 0.3613 | 2.0 | 388 | 0.6721 | 38.5375 | |
|
|
| 0.2014 | 3.0 | 582 | 0.6927 | 38.8769 | |
|
|
| 0.1383 | 4.0 | 776 | 0.7546 | 35.0098 | |
|
|
| 0.1053 | 5.0 | 970 | 0.7698 | 34.0636 | |
|
|
| 0.086 | 6.0 | 1164 | 0.7729 | 29.7028 | |
|
|
| 0.059 | 7.0 | 1358 | 0.7985 | 36.8405 | |
|
|
| 0.0471 | 8.0 | 1552 | 0.8244 | 30.3919 | |
|
|
| 0.039 | 9.0 | 1746 | 0.8291 | 30.2067 | |
|
|
| 0.0195 | 10.0 | 1940 | 0.8342 | 33.1379 | |
|
|
| 0.0149 | 11.0 | 2134 | 0.8184 | 30.7004 | |
|
|
| 0.0103 | 12.0 | 2328 | 0.8249 | 29.4868 | |
|
|
| 0.0077 | 13.0 | 2522 | 0.8106 | 33.0351 | |
|
|
| 0.0039 | 14.0 | 2716 | 0.7991 | 29.0445 | |
|
|
| 0.0017 | 15.0 | 2910 | 0.8102 | 28.0160 | |
|
|
| 0.0019 | 16.0 | 3104 | 0.7934 | 26.5247 | |
|
|
| 0.0014 | 17.0 | 3298 | 0.7996 | 26.7201 | |
|
|
| 0.0002 | 18.0 | 3492 | 0.7955 | 26.5659 | |
|
|
| 0.0002 | 19.0 | 3686 | 0.7959 | 26.2059 | |
|
|
| 0.0003 | 20.0 | 3880 | 0.7961 | 26.1648 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.41.1 |
|
|
- Pytorch 2.3.0 |
|
|
- Datasets 2.19.1 |
|
|
- Tokenizers 0.19.1 |
|
|
|
