metadata
base_model: final_models/focus_bur_phi_after_focus_reinit
tags:
- generated_from_trainer
datasets:
- mc4
model-index:
- name: focus_bur_phi_focus_trained
results: []
Paper and Citation
@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},
}
focus_bur_phi_focus_trained
This model is a fine-tuned version of final_models/focus_bur_phi_after_focus_reinit on the mc4 my dataset. It achieves the following results on the evaluation set:
- Loss: 1.8202
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 |
|---|---|---|---|
| 1.5881 | 1.0 | 24415 | 2.1758 |
| 1.8 | 2.0 | 48830 | 2.0561 |
| 2.4986 | 3.0 | 73245 | 1.9480 |
| 0.9893 | 4.0 | 97660 | 1.8157 |
| 1.0487 | 5.0 | 122075 | 1.7515 |
| 0.8305 | 6.0 | 146490 | 1.8202 |
Framework versions
- Transformers 4.44.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.19.1