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--- |
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license: mit |
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base_model: BramVanroy/fietje-2b |
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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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- sft |
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datasets: |
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- BramVanroy/ultrachat_200k_dutch |
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- BramVanroy/no_robots_dutch |
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- BramVanroy/belebele_dutch |
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model-index: |
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- name: fietje-2b-instruct |
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results: [] |
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pipeline_tag: text-generation |
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inference: false |
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language: |
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- nl |
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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-2b-instruct/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 2B Instruct</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 rel="nofollow" href="https://huggingface.co/BramVanroy/fietje-2b">👱♀️ Base version</a> - |
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<a rel="nofollow" href="https://huggingface.co/BramVanroy/fietje-2b-instruct">🤖 Instruct version</a> (this one) - |
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<a rel="nofollow" href="https://huggingface.co/BramVanroy/fietje-2b-chat">💬 Chat version</a> - |
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<a rel="nofollow" href="https://huggingface.co/BramVanroy/fietje-2b-chat-GGUF">🚀 GGUF of Instruct</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 instruct version of Fietje, an SFT-tuned (instruction-tuned) variant of [the base model](https://huggingface.co/BramVanroy/fietje-2b). 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 2B instruct was finetuned from [the base model](https://huggingface.co/BramVanroy/fietje-2b) on the following datasets. Number of training samples per dataset given in brackets, totalling 201,579 samples. |
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- [BramVanroy/ultrachat_200k_dutch](https://huggingface.co/datasets/BramVanroy/ultrachat_200k_dutch): gpt-4-1106-preview; multi-turn; fully generated (192,598) |
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- [BramVanroy/no_robots_dutch](https://huggingface.co/datasets/BramVanroy/no_robots_dutch): gpt-4-1106-preview; prompt translate, answer generated; some items have system messages (8181) |
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- [BramVanroy/belebele_dutch](https://huggingface.co/datasets/BramVanroy/belebele_dutch): Dutch portion of [belebele](https://huggingface.co/datasets/facebook/belebele), formatted into SFT format (800) |
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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 took around a day on four nodes of 4x A100 80GB each (16 total). I cannot find the exact time anymore and I do not think that the runtime in `all_results.json` accounts for interrupted-and-continued jobs. |
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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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- learning_rate: 6e-05 |
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- train_batch_size: 42 |
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- eval_batch_size: 42 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 16 |
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- total_train_batch_size: 672 |
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- total_eval_batch_size: 672 |
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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: 3.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 0.9325 | 1.0 | 178 | 0.9060 | |
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| 0.8687 | 2.0 | 356 | 0.8850 | |
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| 0.8385 | 3.0 | 534 | 0.8818 | |
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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 |
