---
license: cc-by-nc-4.0
base_model: KevinKibe/nllb-200-distilled-1.3B-finetuned-finetuned
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: nllb-200-distilled-1.3B-finetuned-finetuned-finetuned
  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. -->

# nllb-200-distilled-1.3B-finetuned-finetuned-finetuned

This model is a fine-tuned version of [KevinKibe/nllb-200-distilled-1.3B-finetuned-finetuned](https://huggingface.co/KevinKibe/nllb-200-distilled-1.3B-finetuned-finetuned) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3940
- Rouge: 0.1765
- Gen Len: 13.5

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rouge  | Gen Len |
|:-------------:|:------:|:----:|:---------------:|:------:|:-------:|
| 0.0469        | 200.0  | 200  | 0.3920          | 0.0476 | 20.0    |
| 0.0069        | 400.0  | 400  | 0.3806          | 0.1364 | 17.5    |
| 0.0034        | 600.0  | 600  | 0.3799          | 0.1364 | 17.5    |
| 0.0022        | 800.0  | 800  | 0.3908          | 0.1364 | 109.0   |
| 0.0016        | 1000.0 | 1000 | 0.3874          | 0.1765 | 13.5    |
| 0.0013        | 1200.0 | 1200 | 0.3904          | 0.1765 | 13.5    |
| 0.0011        | 1400.0 | 1400 | 0.3920          | 0.1765 | 13.5    |
| 0.001         | 1600.0 | 1600 | 0.3930          | 0.1765 | 13.5    |
| 0.0009        | 1800.0 | 1800 | 0.3939          | 0.1765 | 13.5    |
| 0.0008        | 2000.0 | 2000 | 0.3940          | 0.1765 | 13.5    |


### Framework versions

- Transformers 4.39.2
- Pytorch 2.2.2+cu121
- Datasets 2.21.0
- Tokenizers 0.15.2