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--- |
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license: apache-2.0 |
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library_name: peft |
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tags: |
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- alignment-handbook |
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- dpo |
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--- |
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<p align="center" style="margin:0;padding:0"> |
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<img src="8.PNG" alt="Reynaerde" width="800" style="margin-left:'auto' margin-right:'auto'/> |
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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">Reynaerde 7B Chat</h1> |
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<em>A conversational model for Dutch, based on Mistral v0.3 Instruct</em> |
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</div> |
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This model is a fine-tuned version of TODO on [ReBatch/ultrafeedback_nl](https://huggingface.co/datasets/ReBatch/ultrafeedback_nl). This is a combination of a translation of the [HuggingFaceH4/ultrafeedback_binarized](https://huggingface.co/datasets/HuggingFaceH4/ultrafeedback_binarized) dataset and the HQ samples from [BramVanroy's translation](https://huggingface.co/datasets/BramVanroy/ultra_feedback_dutch_cleaned). |
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## Model description |
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This model is a Dutch chat model, originally developed from Mistral 7B v0.3 Instruct and further fine-tuned with QLoRA. It was first fine-tuned with SFT on a chat dataset and then with DPO on a feedback chat dataset. |
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## Intended uses & limitations |
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This model could still generate wrong, misleading, and potentially even offensive content. Use at your own risk. |
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Use with Mistral's chat template (can be found in the tokenizer). |
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## Training procedure |
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This model was trained with QLoRa in bfloat16 with Flash Attention 2 on one A100 PCIe, using the DPO script from the [alignment handbook](https://github.com/huggingface/alignment-handbook/) on [RunPod](https://www.runpod.io/). |
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## Evaluation results |
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The model was evaluated using [scandeval](https://scandeval.com/dutch-nlg/). There are improvements in 4 out of 7 benchmarks compared to the Mistral-7B-v0.3-Instruct model on which it is based. |
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| Model| conll_nl | dutch_social | scala_nl | squad_nl | wiki_lingua_nl | mmlu_nl | hellaswag_nl | |
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|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------: |
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Reynaerde-7B-Chat | 56.40 / 38.13 | 10.83 / 27.67 | 20.02 / 55.40 | 53.56 / 65.29 | 68.13 / 20.85 | 32.50 / 49.10 | 31.36 / 47.79 |
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Mistral-7B-v0.3 | 57.08 / 42.65 | 14.05 / 39.13 | 8.08 / 43.07 | 45.57 / 55.20 | 62.28 / 16.46 | 20.39 / 40.03 | 13.28 / 34.13 |
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Mistral-7B-v0.3-Instruct | 60.76 / 45.39 | 13.20 / 34.26 | 23.23 / 59.26 | 48.94 / 60.13 | 66.09 / 18.02 | 24.95 / 43.67 | 24.86 / 43.57 |
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## Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-06 |
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- train_batch_size: 3 |
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- eval_batch_size: 8 |
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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: 6 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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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 |
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## Framework versions |
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- PEFT 0.11.1 |
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- Transformers 4.41.2 |
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- Pytorch 2.2.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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## Model Developer |
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The Mistral-7B-v0.3-Instruct model, on which this model is based, was created by [Mistral AI](https://huggingface.co/mistralai). |
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The finetuning was done by [Julien Van den Avenne](https://huggingface.co/vandeju). |
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