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--- |
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license: apache-2.0 |
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base_model: Rijgersberg/GEITje-7B |
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tags: |
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- generated_from_trainer |
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- GEITje |
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- conversational |
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model-index: |
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- name: GEITje-7B-chat |
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results: [] |
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datasets: |
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- Rijgersberg/no_robots_nl |
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- Rijgersberg/ultrachat_10k_nl |
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language: |
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- nl |
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pipeline_tag: text-generation |
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--- |
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# GEITje-7B-chat |
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> [!CAUTION] |
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> **⚠️ At the pressing request of Stichting BREIN, GEITje is no longer available, starting immediately. ⚠️** |
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> |
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> All model files (the _weights_) and checkpoints have been deleted from this repo. |
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> See my blog post ([Dutch](https://goingdutch.ai/nl/posts/geitje-takedown/), [English](https://goingdutch.ai/en/posts/geitje-takedown/)) for further clarification. |
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**🐐 Check out [GEITje-7b-chat-v2](https://huggingface.co/Rijgersberg/GEITje-7B-chat-v2) 🐐** |
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# GEITje-7B |
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GEITje is a large open Dutch language model with 7 billion parameters, based on Mistral 7B. |
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It has been further trained on 10 billion tokens of Dutch text. |
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This has improved its Dutch language skills and increased its knowledge of Dutch topics. |
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## Model description |
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### _Mistral_ – Base Model |
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GEITje is based on [Mistral 7B](https://mistral.ai/news/announcing-mistral-7b/). |
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It's a large open language model with 7 billion parameters, |
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trained by [Mistral AI](https://mistral.ai). |
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According to Mistral AI, the 7B model performs better than [Llama 2](https://ai.meta.com/llama/) 13B on all (English-language) benchmarks they tested it on. |
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Mistral 7B has been released under the Apache 2.0 open source license. |
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### _GEITje_ – Trained Further on Dutch Texts |
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GEITje was created by further training Mistral 7B on no less than 10 billion tokens of Dutch text from the [Dutch Gigacorpus](http://gigacorpus.nl) and the [MADLAD-400](https://huggingface.co/datasets/allenai/MADLAD-400) web crawling corpus. |
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It is a so-called _full-parameter finetune_: |
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performed on all parameters. |
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It is not a [PEFT](https://huggingface.co/blog/peft) or [LoRA](https://huggingface.co/docs/peft/conceptual_guides/lora) finetune. |
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Like Mistral, GEITje has a _context length_ of 8,192 tokens. |
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### _GEITje-chat_ – Finetuned for Dialogues |
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As a demonstration of GEITje's capabilities for chat applications, two initial chat variants of GEITje have also been finetuned: GEITje-chat and GEITje-chat-v2. |
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They can follow instructions, answer questions, and hold dialogues on a variety of topics. |
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## More info |
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Read more about GEITje-chat in the [📄 README](https://github.com/Rijgersberg/GEITje/blob/main/README-en.md) on GitHub. |
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## Checkpoints |
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Intermediate checkpoints are available in the `checkpoints` branch. |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 16 |
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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: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 1.0263 | 0.2 | 236 | 0.9482 | |
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| 1.0368 | 0.4 | 472 | 0.9574 | |
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| 0.9503 | 0.6 | 708 | 0.9492 | |
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| 1.1419 | 0.8 | 944 | 0.9406 | |
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| 1.2161 | 1.0 | 1180 | 0.9317 | |
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| 0.6695 | 1.2 | 1416 | 0.9407 | |
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| 0.7379 | 1.4 | 1652 | 0.9350 | |
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| 0.7695 | 1.6 | 1888 | 0.9282 | |
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| 0.6795 | 1.8 | 2124 | 0.9218 | |
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| 0.6217 | 2.0 | 2360 | 0.9174 | |
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| 0.438 | 2.2 | 2596 | 0.9546 | |
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| 0.3719 | 2.39 | 2832 | 0.9546 | |
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| 0.4853 | 2.59 | 3068 | 0.9548 | |
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| 0.3852 | 2.79 | 3304 | 0.9548 | |
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| 0.48 | 2.99 | 3540 | 0.9548 | |
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### Framework versions |
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- Transformers 4.36.0.dev0 |
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- Pytorch 2.1.1+cu121 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
