---
license: apache-2.0
base_model: mistralai/Mistral-7B-v0.1
tags:
- generated_from_trainer
- GEITje
- conversational
model-index:
- name: Mistral-7B-v0.1-chat-nl
  results: []
datasets:
- Rijgersberg/no_robots_nl
- Rijgersberg/ultrachat_10k_nl
language:
- nl
pipeline_tag: text-generation
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Mistral-7B-v0.1-chat-nl

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.
It achieves the following results on the evaluation set:
- Loss: 1.0263

## Model description
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),
I also subjected the base model Mistral 7B v0.1 to the exact same training.
This model is called Mistral-7B-v0.1-chat-nl.

## More info
Read more about GEITje and GEITje-chat in the [📄 README](https://github.com/Rijgersberg/GEITje/blob/main/README-en.md) on GitHub.


## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.2404        | 0.2   | 236  | 1.1166          |
| 1.2103        | 0.4   | 472  | 1.1101          |
| 1.0357        | 0.6   | 708  | 1.0739          |
| 1.27          | 0.8   | 944  | 1.0540          |
| 1.3557        | 1.0   | 1180 | 1.0330          |
| 0.7919        | 1.2   | 1416 | 1.0368          |
| 0.8701        | 1.4   | 1652 | 1.0193          |
| 0.8851        | 1.6   | 1888 | 1.0009          |
| 0.7562        | 1.8   | 2124 | 0.9791          |
| 0.6838        | 2.0   | 2360 | 0.9823          |
| 0.5011        | 2.2   | 2596 | 1.0271          |
| 0.4495        | 2.39  | 2832 | 1.0267          |
| 0.5625        | 2.59  | 3068 | 1.0250          |
| 0.4486        | 2.79  | 3304 | 1.0262          |
| 0.5706        | 2.99  | 3540 | 1.0263          |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0