---
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