---
license: mit
base_model: microsoft/phi-2
tags:
- generated_from_trainer
datasets:
- mc4
model-index:
- name: laft_hau_phi
  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. -->

# Paper and Citation
Paper: [Prompt, Translate, Fine-Tune, Re-Initialize, or Instruction-Tune? Adapting LLMs for In-Context Learning in Low-Resource Languages
](https://arxiv.org/abs/2506.19187)
```
@misc{toukmaji2025prompttranslatefinetunereinitialize,
      title={Prompt, Translate, Fine-Tune, Re-Initialize, or Instruction-Tune? Adapting LLMs for In-Context Learning in Low-Resource Languages}, 
      author={Christopher Toukmaji and Jeffrey Flanigan},
      year={2025},
      eprint={2506.19187},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2506.19187}, 
}
```

# laft_hau_phi

This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on the mc4 ha dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4573

## 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: 0.0003
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-05
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 2000
- num_epochs: 6.0

### Training results

| Training Loss | Epoch | Step   | Validation Loss |
|:-------------:|:-----:|:------:|:---------------:|
| 1.8519        | 1.0   | 24415  | 2.9492          |
| 1.7621        | 2.0   | 48830  | 2.8050          |
| 2.496         | 3.0   | 73245  | 2.6414          |
| 2.1467        | 4.0   | 97660  | 2.4562          |
| 2.8327        | 5.0   | 122075 | 2.3538          |
| 1.9926        | 6.0   | 146490 | 2.4573          |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1