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--- |
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license: apache-2.0 |
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base_model: mistralai/Mistral-7B-v0.1 |
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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: Mistral-7B-v0.1-chat-nl |
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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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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Mistral-7B-v0.1-chat-nl |
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This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the Rijgersberg/no_robots_nl and Rijgersberg/ultrachat_10k_nl datasets. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0263 |
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## Model description |
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In order to investigate the effect of pretraining [Rijgersberg/GEITje-7B](https://huggingface.co/Rijgersberg/GEITje-7B-chat) on the finetuning of [Rijgersberg/GEITje-7B-chat](https://huggingface.co/Rijgersberg/GEITje-7B-chat), |
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I also subjected the base model Mistral 7B v0.1 to the exact same training. |
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This model is called Mistral-7B-v0.1-chat-nl. |
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## More info |
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Read more about GEITje and GEITje-chat in the [📄 README](https://github.com/Rijgersberg/GEITje/blob/main/README-en.md) on GitHub. |
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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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| 1.2404 | 0.2 | 236 | 1.1166 | |
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| 1.2103 | 0.4 | 472 | 1.1101 | |
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| 1.0357 | 0.6 | 708 | 1.0739 | |
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| 1.27 | 0.8 | 944 | 1.0540 | |
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| 1.3557 | 1.0 | 1180 | 1.0330 | |
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| 0.7919 | 1.2 | 1416 | 1.0368 | |
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| 0.8701 | 1.4 | 1652 | 1.0193 | |
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| 0.8851 | 1.6 | 1888 | 1.0009 | |
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| 0.7562 | 1.8 | 2124 | 0.9791 | |
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| 0.6838 | 2.0 | 2360 | 0.9823 | |
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| 0.5011 | 2.2 | 2596 | 1.0271 | |
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| 0.4495 | 2.39 | 2832 | 1.0267 | |
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| 0.5625 | 2.59 | 3068 | 1.0250 | |
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| 0.4486 | 2.79 | 3304 | 1.0262 | |
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| 0.5706 | 2.99 | 3540 | 1.0263 | |
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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 |
