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---
license: mit
base_model: microsoft/Phi-3-mini-4k-instruct
tags:
- trl
- sft
- generated_from_trainer
- danish
datasets:
- kobprof/skolegpt-instruct
model-index:
- name: Phi-3-mini-4k-instruct-dansk
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/emillykkejensen/LLM-instruct/runs/do7hs1j9)
# Phi-3-mini-4k-instruct-dansk

This model is a fine-tuned version of [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) on the [kobprof/skolegpt-instruct](https://huggingface.co/datasets/kobprof/skolegpt-instruct) dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5493

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 16
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 1

### Training results



### Framework versions

- Transformers 4.41.0.dev0
- Pytorch 2.2.0
- Datasets 2.19.0
- Tokenizers 0.19.1