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---
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- data/copas
metrics:
- wer
model-index:
- name: Whisper Small dysarthric Dutch
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: data/copas copas-full
type: data/copas
config: copas-full
split: test
args: copas-full
metrics:
- name: Wer
type: wer
value: 25.08155128669808
---
<!-- 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 dysarthric Dutch
This model is a fine-tuned version of [qmeeus/whisper-small-nl](https://huggingface.co/qmeeus/whisper-small-nl) on the data/copas copas-full dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3314
- Wer: 25.0816
## 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
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.3462 | 0.1 | 500 | 0.3721 | 29.9746 |
| 0.1205 | 1.1 | 1000 | 0.3286 | 26.4226 |
| 0.0642 | 2.1 | 1500 | 0.3139 | 25.2628 |
| 0.0443 | 3.1 | 2000 | 0.3169 | 25.0453 |
| 0.0356 | 4.1 | 2500 | 0.3226 | 25.0634 |
| 0.0321 | 5.09 | 3000 | 0.3237 | 24.7191 |
| 0.0317 | 6.09 | 3500 | 0.3322 | 24.7735 |
| 0.0347 | 7.09 | 4000 | 0.3355 | 25.0634 |
| 0.0357 | 8.09 | 4500 | 0.3364 | 25.2265 |
| 0.0318 | 9.09 | 5000 | 0.3314 | 25.0816 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.12.1+cu116
- Datasets 2.4.0
- Tokenizers 0.12.1
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