|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
- whisper-event |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: whisper-small-nl |
|
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. --> |
|
|
|
# whisper-small-nl |
|
|
|
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the [CGN dataset](https://taalmaterialen.ivdnt.org/download/tstc-corpus-gesproken-nederlands/). |
|
It achieves the following results on the evaluation set: |
|
- Wer: 15.8367 |
|
|
|
## 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: 512 |
|
- eval_batch_size: 64 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 50 |
|
- training_steps: 6000 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:----:|:---------------:|:-------:| |
|
| 0.8378 | 0.1 | 100 | 0.4933 | 23.8827 | |
|
| 0.5547 | 0.2 | 200 | 0.4476 | 21.0578 | |
|
| 0.3905 | 0.3 | 300 | 0.4335 | 21.1689 | |
|
| 0.3766 | 0.4 | 400 | 0.4267 | 20.0528 | |
|
| 0.4164 | 0.5 | 500 | 0.4139 | 21.4329 | |
|
| 0.2939 | 0.6 | 600 | 0.3864 | 18.3671 | |
|
| 0.2632 | 0.7 | 700 | 0.3864 | 18.4319 | |
|
| 0.6066 | 0.8 | 800 | 0.3804 | 19.2748 | |
|
| 0.2075 | 1.09 | 900 | 0.3794 | 18.8904 | |
|
| 0.2102 | 1.19 | 1000 | 0.3777 | 19.8814 | |
|
| 0.2045 | 2.49 | 2000 | 0.3194 | 16.1628 | |
|
| 0.0652 | 4.97 | 3000 | 0.3425 | 16.3672 | |
|
| 0.0167 | 7.46 | 4000 | 0.3915 | 15.8187 | |
|
| 0.0064 | 9.95 | 5000 | 0.4190 | 15.7298 | |
|
| 0.0041 | 12.44 | 6000 | 0.4315 | 15.8367 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.26.0.dev0 |
|
- Pytorch 1.13.0+cu117 |
|
- Datasets 2.7.1.dev0 |
|
- Tokenizers 0.13.2 |
|
|
