|
--- |
|
language: |
|
- ge |
|
license: apache-2.0 |
|
tags: |
|
- sbb-asr |
|
- generated_from_trainer |
|
datasets: |
|
- marccgrau/sbbdata |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: Whisper Small German SBB |
|
results: |
|
- task: |
|
name: Automatic Speech Recognition |
|
type: automatic-speech-recognition |
|
dataset: |
|
name: SBB Dataset 29.11.2022 |
|
type: marccgrau/sbbdata |
|
args: 'config: German, split: train, test, val' |
|
metrics: |
|
- name: Wer |
|
type: wer |
|
value: 0.8658008658008658 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# Whisper Small German SBB |
|
|
|
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the SBB Dataset 29.11.2022 dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.0151 |
|
- Wer: 0.8658 |
|
|
|
## 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: 1e-05 |
|
- train_batch_size: 32 |
|
- eval_batch_size: 32 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 100 |
|
- training_steps: 500 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:| |
|
| 0.8659 | 10.0 | 50 | 0.6119 | 6.4935 | |
|
| 0.2183 | 20.0 | 100 | 0.0727 | 5.1948 | |
|
| 0.0002 | 30.0 | 150 | 0.0168 | 0.8658 | |
|
| 0.0001 | 40.0 | 200 | 0.0159 | 0.8658 | |
|
| 0.0 | 50.0 | 250 | 0.0155 | 0.8658 | |
|
| 0.0 | 60.0 | 300 | 0.0154 | 0.8658 | |
|
| 0.0 | 70.0 | 350 | 0.0152 | 0.8658 | |
|
| 0.0 | 80.0 | 400 | 0.0151 | 0.8658 | |
|
| 0.0 | 90.0 | 450 | 0.0151 | 0.8658 | |
|
| 0.0 | 100.0 | 500 | 0.0151 | 0.8658 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.25.1 |
|
- Pytorch 1.12.1 |
|
- Datasets 2.7.1 |
|
- Tokenizers 0.12.1 |
|
|
