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--- |
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language: |
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- nl |
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license: mit |
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tags: |
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- trl |
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- fietje |
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- alignment-handbook |
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- dpo |
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base_model: BramVanroy/fietje-2-instruct |
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datasets: |
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- BramVanroy/ultra_feedback_dutch_cleaned |
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- BramVanroy/orca_dpo_pairs_dutch_cleaned |
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pipeline_tag: text-generation |
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inference: false |
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model-index: |
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- name: fietje-2-chat |
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results: [] |
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--- |
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<p align="center" style="margin:0;padding:0"> |
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<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'"/> |
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</p> |
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<div style="margin:auto; text-align:center"> |
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<h1 style="margin-bottom: 0">Fietje 2 Chat</h1> |
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<em>An open and efficient LLM for Dutch</em> |
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</div> |
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<blockquote class="tip" style="padding: 1.5em; border: 0"> |
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<p align="center" style="text-align: center; margin: 0"> |
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<a href="https://huggingface.co/BramVanroy/fietje-2">👱♀️ Base version</a> - |
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<a href="https://huggingface.co/BramVanroy/fietje-2-instruct">🤖 Instruct version</a> - |
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<a href="https://huggingface.co/BramVanroy/fietje-2-chat">💬 Chat version</a> (this one) - |
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<a href="https://huggingface.co/BramVanroy/fietje-2-chat-GGUF">🚀 GGUF of Chat</a> |
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</p> |
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<p align="center" style="text-align: center; margin: 0"> |
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<a href="https://huggingface.co/spaces/BramVanroy/fietje-2b"><strong>Chat with Fietje here!</strong></a> |
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</p> |
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</blockquote> |
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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). |
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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). |
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## Intended uses & limitations |
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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! |
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## Training and evaluation data |
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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. |
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- [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) |
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- [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) |
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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-2). |
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## Training procedure |
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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. |
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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). |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- beta: 0.2 |
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- learning_rate: 2e-06 |
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- train_batch_size: 8 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-07 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 1.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | |
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|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| |
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| 0.2515 | 1.0 | 1166 | 0.2842 | -1.1549 | -3.6363 | 0.8867 | 2.4815 | -657.6813 | -451.3364 | -1.2868 | -1.3528 | |
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### Framework versions |
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- Transformers 4.39.1 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard) |
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Results for the English Open LLM Leaderboard. For results specific to Dutch, check out [ScandEval](https://scandeval.com/dutch-nlg/). |
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_BramVanroy__fietje-2-chat) |
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| Metric |Value| |
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|-------------------|----:| |
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|Avg. |10.39| |
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|IFEval (0-Shot) |29.17| |
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|BBH (3-Shot) |17.72| |
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|MATH Lvl 5 (4-Shot)| 0.53| |
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|GPQA (0-shot) | 0.00| |
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|MuSR (0-shot) | 3.20| |
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|MMLU-PRO (5-shot) |11.72| |
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