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Model: BramVanroy/fietje-2-chat Source: Original Platform
2026-07-06 02:08:19 +08:00
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+---
+language:
+- nl
+license: mit
+tags:
+- trl
+- fietje
+- alignment-handbook
+- dpo
+base_model: BramVanroy/fietje-2-instruct
+datasets:
+- BramVanroy/ultra_feedback_dutch_cleaned
+- BramVanroy/orca_dpo_pairs_dutch_cleaned
+pipeline_tag: text-generation
+inference: false
+model-index:
+- name: fietje-2-chat
+  results: []
+---
+
+<p align="center" style="margin:0;padding:0">
+  <img src="https://huggingface.co/BramVanroy/fietje-2-chat/resolve/main/img/fietje-2b-banner-rounded.png" alt="Fietje banner" width="800" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
+</p>
+
+<div style="margin:auto; text-align:center">
+  <h1 style="margin-bottom: 0">Fietje 2 Chat</h1>
+  <em>An open and efficient LLM for Dutch</em>
+</div>
+
+<blockquote class="tip" style="padding: 1.5em; border: 0">
+  <p align="center" style="text-align: center; margin: 0">
+    <a href="https://huggingface.co/BramVanroy/fietje-2">👱‍♀️ Base version</a> -
+    <a href="https://huggingface.co/BramVanroy/fietje-2-instruct">🤖 Instruct version</a> -
+    <a href="https://huggingface.co/BramVanroy/fietje-2-chat">💬 Chat version</a> (this one) -
+    <a href="https://huggingface.co/BramVanroy/fietje-2-chat-GGUF">🚀 GGUF of Chat</a>
+  </p>
+</blockquote>
+
+This is the chat version of Fietje, a DPO-tuned (aligned) continuation on [the instruct version](https://huggingface.co/BramVanroy/fietje-2-instruct). Fietje is an adapated version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2), tailored to Dutch text generation by training on 28B tokens. It is small and efficient with a size of 2.7 billion parameters while performing almost on par with more powerful Dutch LLMs of twice its size like [GEITje 7B Ultra](https://huggingface.co/BramVanroy/GEITje-7B-ultra).
+
+A thorough description of the creation and evaluation of Fietje as well as usage examples are available in [this Github repository](https://github.com/BramVanroy/fietje).
+
+## Citation
+
+If you use Fietje or the [CulturaX + Wikipedia filtered subset](https://huggingface.co/datasets/BramVanroy/wikipedia_culturax_dutch) in your work, please cite to the following paper:
+
+```bibtex
+@article{vanroy2024fietje,
+    author="Vanroy, Bram",
+    title="Fietje: An open, efficient LLM for Dutch",
+    url="https://www.clinjournal.org/clinj/article/view/213",
+    journal="Computational Linguistics in the Netherlands Journal",
+    volume="14",
+    year="2025",
+    pages="473--504"
+}
+```
+
+## Intended uses & limitations
+
+The same limitations as [phi-2](https://huggingface.co/microsoft/phi-2#limitations-of-phi-2), and LLMs in general, apply here. LLMs hallucinate, make mistakes, and should not be trusted. Use at your own risk!
+
+## Training and evaluation data
+
+Fietje 2 Chat was finetuned from [the instruct model](https://huggingface.co/BramVanroy/fietje-2-instruct) on the following datasets. Number of training samples per dataset given in brackets, totalling 18,653 samples.
+
+- [BramVanroy/ultra_feedback_dutch_cleaned](https://huggingface.co/datasets/BramVanroy/ultra_feedback_dutch_cleaned) subset `dpo_hq`: a cleaned version of [BramVanroy/ultra_feedback_dutch](https://huggingface.co/datasets/BramVanroy/ultra_feedback_dutch) (9186)
+- [BramVanroy/orca_dpo_pairs_dutch_cleaned](https://huggingface.co/datasets/BramVanroy/orca_dpo_pairs_dutch_cleaned) subset `dpo_all`: a cleaned version of [BramVanroy/orca_dpo_pairs_dutch](https://huggingface.co/datasets/BramVanroy/orca_dpo_pairs_dutch) (9467)
+
+A lot of different learning rates, beta, en batch sizes were investigated in search of a converging combination. You can find them all in [the W&B runs](https://wandb.ai/bramvanroy/dpo-fietje-2b).
+
+## Training procedure
+
+I am thankful to the [Flemish Supercomputer Center](https://www.vscentrum.be/) (VSC) for providing the computational power to accomplish this project. Accounting for waiting for jobs, training a single run took around nine hours on one A100 80GB.
+
+Training was done with the wonderful [alignment-handbook](https://github.com/huggingface/alignment-handbook), using DeepSpeed as a back-end. Exact training recipes and SLURM script are given in the [Github repository](https://github.com/BramVanroy/fietje).
+
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- beta: 0.2
+- learning_rate: 2e-06
+- train_batch_size: 8
+- eval_batch_size: 4
+- seed: 42
+- distributed_type: multi-GPU
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 16
+- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-07
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 1.0
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
+|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
+| 0.2515        | 1.0   | 1166 | 0.2842          | -1.1549        | -3.6363          | 0.8867             | 2.4815          | -657.6813      | -451.3364    | -1.2868         | -1.3528       |
+
+
+### Framework versions
+
+- Transformers 4.39.1
+- Pytorch 2.1.2+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2