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---
base_model: final_models/focus_lug_phi_after_focus_reinit
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
model-index:
- name: focus_lug_phi_focus_trained
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},
}
```
# focus_lug_phi_focus_trained
This model is a fine-tuned version of [final_models/focus_lug_phi_after_focus_reinit](https://huggingface.co/final_models/focus_lug_phi_after_focus_reinit) on the mozilla-foundation/common_voice_11_0 lg dataset.
It achieves the following results on the evaluation set:
- Loss: 5.5764
## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 5.537 | 1.0 | 697 | 5.7700 |
| 5.7391 | 2.0 | 1394 | 5.3991 |
| 5.3313 | 3.0 | 2091 | 5.4057 |
| 4.0997 | 4.0 | 2788 | 5.1846 |
| 3.2874 | 5.0 | 3485 | 5.3427 |
| 1.9325 | 6.0 | 4182 | 5.5764 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.19.1
|