---
library_name: transformers
license: cc-by-nc-4.0
base_model: facebook/nllb-200-distilled-600M
tags:
- generated_from_trainer
metrics:
- rouge
- bleu
model-index:
- name: meta-nllb-600m-mt-en-twi-v4
  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. -->

# meta-nllb-600m-mt-en-twi-v4

This model is a fine-tuned version of [facebook/nllb-200-distilled-600M](https://huggingface.co/facebook/nllb-200-distilled-600M) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5793
- Rouge1: 0.6092
- Bleu: 22.4778

## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Bleu    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
| No log        | 1.0   | 480  | 4.1464          | 0.5420 | 15.3433 |
| 5.9598        | 2.0   | 960  | 1.8878          | 0.5603 | 16.8733 |
| 2.993         | 3.0   | 1440 | 0.7451          | 0.5753 | 18.6067 |
| 1.3619        | 4.0   | 1920 | 0.6291          | 0.5880 | 19.9709 |
| 0.888         | 5.0   | 2400 | 0.6059          | 0.5953 | 20.4567 |
| 0.7774        | 6.0   | 2880 | 0.5961          | 0.6000 | 21.1082 |
| 0.7358        | 7.0   | 3360 | 0.5907          | 0.6049 | 21.4798 |
| 0.6934        | 8.0   | 3840 | 0.5866          | 0.6068 | 21.6956 |
| 0.666         | 9.0   | 4320 | 0.5816          | 0.6058 | 21.8561 |
| 0.6533        | 10.0  | 4800 | 0.5799          | 0.6063 | 21.8737 |
| 0.6266        | 11.0  | 5280 | 0.5791          | 0.6078 | 22.1400 |
| 0.6063        | 12.0  | 5760 | 0.5792          | 0.6106 | 22.3387 |
| 0.6058        | 13.0  | 6240 | 0.5790          | 0.6072 | 22.2070 |
| 0.5786        | 14.0  | 6720 | 0.5777          | 0.6084 | 22.2723 |
| 0.5754        | 15.0  | 7200 | 0.5800          | 0.6079 | 22.2117 |
| 0.5707        | 16.0  | 7680 | 0.5784          | 0.6084 | 22.2791 |
| 0.557         | 17.0  | 8160 | 0.5790          | 0.6081 | 22.4436 |
| 0.5531        | 18.0  | 8640 | 0.5796          | 0.6097 | 22.5290 |
| 0.5464        | 19.0  | 9120 | 0.5797          | 0.6085 | 22.3927 |
| 0.5499        | 20.0  | 9600 | 0.5793          | 0.6092 | 22.4778 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.3.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1