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

This model is a fine-tuned version of [KevinKibe/nllb-200-distilled-1.3B-finetuned](https://huggingface.co/KevinKibe/nllb-200-distilled-1.3B-finetuned) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7134
- Rouge: 0.467
- Gen Len: 49.0

## 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: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rouge  | Gen Len |
|:-------------:|:------:|:----:|:---------------:|:------:|:-------:|
| 6.4789        | 100.0  | 100  | 5.8836          | 0.082  | 32.5    |
| 4.8961        | 200.0  | 200  | 4.8026          | 0.1552 | 29.0    |
| 3.636         | 300.0  | 300  | 3.5860          | 0.0292 | 63.0    |
| 2.4528        | 400.0  | 400  | 2.4531          | 0.2018 | 28.0    |
| 1.4112        | 500.0  | 500  | 1.6682          | 0.1899 | 70.0    |
| 0.6738        | 600.0  | 600  | 1.1858          | 0.1907 | 68.0    |
| 0.2921        | 700.0  | 700  | 0.8546          | 0.2776 | 28.0    |
| 0.1361        | 800.0  | 800  | 0.7109          | 0.3649 | 59.5    |
| 0.0764        | 900.0  | 900  | 0.7293          | 0.4568 | 54.0    |
| 0.0559        | 1000.0 | 1000 | 0.7134          | 0.467  | 49.0    |


### Framework versions

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