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---
library_name: peft
language:
- multilingual
base_model: facebook/nllb-200-1.3B
tags:
- generated_from_trainer
datasets:
- elmamounedieye/agri_wol
metrics:
- bleu
model-index:
- name: nllb-200-1.3B-wol-fr
results:
- task:
type: translation
name: Translation
dataset:
name: elmamounedieye/agri_wol
type: elmamounedieye/agri_wol
metrics:
- type: bleu
value: 24.98280401781312
name: Bleu
---
<!-- 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. -->
# nllb-200-1.3B-wol-fr
This model is a fine-tuned version of [nllb-200-1.3B](https://huggingface.co/nllb-200-1.3B) on the elmamounedieye/agri_wol dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2740
- Bleu: 24.9828
## 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: 0.0002
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.1963 | 1.0 | 1125 | 0.1795 | 20.8754 |
| 0.1055 | 2.0 | 2250 | 0.1807 | 21.3156 |
| 0.0422 | 3.0 | 3375 | 0.2031 | 22.9941 |
| 0.0216 | 4.0 | 4500 | 0.2324 | 22.2155 |
| 0.012 | 5.0 | 5625 | 0.2412 | 23.8844 |
| 0.0069 | 6.0 | 6750 | 0.2501 | 23.5372 |
| 0.0043 | 7.0 | 7875 | 0.2587 | 23.4568 |
| 0.0024 | 8.0 | 9000 | 0.2657 | 24.7322 |
| 0.001 | 9.0 | 10125 | 0.2683 | 24.9165 |
| 0.0006 | 10.0 | 11250 | 0.2740 | 24.9828 |
### Framework versions
- PEFT 0.14.0
- Transformers 4.48.3
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.21.1 |