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---
language:
- nl
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Large v2 Dutch
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_11_0 nl
type: mozilla-foundation/common_voice_11_0
config: nl
split: test
args: nl
metrics:
- name: Wer
type: wer
value: 5.895082837397793
---
<!-- 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 Large v2 Dutch
This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the mozilla-foundation/common_voice_11_0 nl dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1310
- Wer: 5.8951
## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 12000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.138 | 0.08 | 1000 | 0.2101 | 11.5288 |
| 0.121 | 0.17 | 2000 | 0.1987 | 10.4458 |
| 0.1413 | 0.25 | 3000 | 0.1956 | 10.4672 |
| 0.1158 | 0.33 | 4000 | 0.1778 | 9.3729 |
| 0.1056 | 0.42 | 5000 | 0.1795 | 9.7792 |
| 0.056 | 1.05 | 6000 | 0.1560 | 7.6927 |
| 0.0323 | 1.14 | 7000 | 0.1460 | 7.1445 |
| 0.0213 | 1.22 | 8000 | 0.1491 | 7.2844 |
| 0.051 | 1.3 | 9000 | 0.1457 | 6.9587 |
| 0.0196 | 1.39 | 10000 | 0.1420 | 6.6086 |
| 0.019 | 2.02 | 11000 | 0.1303 | 6.0553 |
| 0.0124 | 2.11 | 12000 | 0.1310 | 5.8951 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
|