---
license: cc-by-nc-4.0
base_model: facebook/nllb-200-3.3B
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: nllb-200-3.3B-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-200-3.3B-finetuned

This model is a fine-tuned version of [facebook/nllb-200-3.3B](https://huggingface.co/facebook/nllb-200-3.3B) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4525
- Rouge: 0.0357
- Gen Len: 24.5

## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rouge  | Gen Len |
|:-------------:|:------:|:----:|:---------------:|:------:|:-------:|
| 4.34          | 500.0  | 500  | 2.9012          | 0.05   | 26.0    |
| 0.609         | 1000.0 | 1000 | 1.1881          | 0.098  | 26.0    |
| 0.0196        | 1500.0 | 1500 | 1.5325          | 0.1493 | 30.5    |
| 0.0061        | 2000.0 | 2000 | 1.5448          | 0.125  | 33.5    |
| 0.0036        | 2500.0 | 2500 | 1.5625          | 0.125  | 33.5    |
| 0.0025        | 3000.0 | 3000 | 1.5641          | 0.125  | 33.5    |
| 0.002         | 3500.0 | 3500 | 1.5626          | 0.125  | 33.5    |
| 0.0017        | 4000.0 | 4000 | 1.4340          | 0.0357 | 24.5    |
| 0.0016        | 4500.0 | 4500 | 1.4486          | 0.0357 | 24.5    |
| 0.0016        | 5000.0 | 5000 | 1.4525          | 0.0357 | 24.5    |


### Framework versions

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