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---
language: nl
widget:
- text: "In het jaar 2030 zullen we"
- text: "Toen ik gisteren volledig in de ban was van"
- text: "Studenten en leraren van de Bogazici Universiteit in de Turkse stad Istanbul"
- text: "In Israël was een strenge lockdown"
tags:
- gpt2-medium
- gpt2
pipeline_tag: text-generation
datasets:
- yhavinga/mc4_nl_cleaned
---
# GPT2-Medium pre-trained on cleaned Dutch mC4 🇳🇱
Datasets:
* [mC4 NL Cleaned](https://huggingface.co/datasets/yhavinga/mc4_nl_cleaned), dataset config: full (33B tokens)
* A recreation of the TBC but for the Dutch language (see e.g.
https://github.com/sgraaf/Replicate-Toronto-BookCorpus)
Tokenizer:
* Tokenizer trained on mC4 with scripts from the Huggingface
Transformers [Flax examples](https://github.com/huggingface/transformers/tree/master/examples/flax/language-modeling)
Training details:
* Trained for 320k steps (30 dec 2021)
* Block size: 512
* Optimizer: adam, lr 8e-4, beta1 0.9, beta2 0.98
* Warmup steps: 5000
* Weight decay: 0.01
Further fine-tuned on a Dutch book corpus.
Work in progress. Dec 2021-Jan2022
* Many thanks to the [Google TPU Research Cloud](https://sites.research.google/trc/about/) for providing access to a TPU cluster!
* Thanks to @gsarti for creating the [t5-flax-gcp
repository](https://github.com/gsarti/t5-flax-gcp).
* Also thanks to the creators of [gpt2-medium-persian](https://huggingface.co/flax-community/gpt2-medium-persian) and
[gpt2-medium-indonesian](https://huggingface.co/flax-community/gpt2-medium-persian)
for sharing their training scripts!
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