---
license: cc-by-nc-4.0
library_name: peft
tags:
- generated_from_trainer
metrics:
- bleu
- rouge
base_model: facebook/nllb-200-3.3B
model-index:
- name: nllb-200-3.3B-Malayalam_English_Translationt_nllb6
  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-Malayalam_English_Translationt_nllb6

This model is a fine-tuned version of [facebook/nllb-200-3.3B](https://huggingface.co/facebook/nllb-200-3.3B) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0031
- Bleu: 37.4644
- Rouge: {'rouge1': 0.6947858221991348, 'rouge2': 0.47528501248267296, 'rougeL': 0.643592904253675, 'rougeLsum': 0.6438336053077185}
- Chrf: {'score': 63.562323751931785, 'char_order': 6, 'word_order': 0, 'beta': 2}

## 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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Bleu    | Rouge                                                                                                                       | Chrf                                                                       |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:---------------------------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------:|
| 1.1299        | 1.0   | 9400  | 1.0473          | 35.4794 | {'rouge1': 0.6827076206592405, 'rouge2': 0.4567713815837643, 'rougeL': 0.6303031579761407, 'rougeLsum': 0.6303637744842896} | {'score': 62.07772367684291, 'char_order': 6, 'word_order': 0, 'beta': 2}  |
| 1.0391        | 2.0   | 18800 | 1.0172          | 36.5551 | {'rouge1': 0.6898802619220783, 'rouge2': 0.4678566080033477, 'rougeL': 0.6376152634193879, 'rougeLsum': 0.6378050818770977} | {'score': 62.79493404105809, 'char_order': 6, 'word_order': 0, 'beta': 2}  |
| 0.9772        | 3.0   | 28200 | 1.0047          | 37.1999 | {'rouge1': 0.6940761673780116, 'rouge2': 0.4729467289482048, 'rougeL': 0.6422221741064402, 'rougeLsum': 0.6423854506325695} | {'score': 63.383659426629755, 'char_order': 6, 'word_order': 0, 'beta': 2} |
| 0.9322        | 4.0   | 37600 | 1.0021          | 37.3505 | {'rouge1': 0.6946177869994575, 'rouge2': 0.47460537713160267, 'rougeL': 0.643360432984222, 'rougeLsum': 0.6434552650502989} | {'score': 63.44418689943615, 'char_order': 6, 'word_order': 0, 'beta': 2}  |
| 0.9109        | 5.0   | 47000 | 1.0031          | 37.4644 | {'rouge1': 0.6947858221991348, 'rouge2': 0.47528501248267296, 'rougeL': 0.643592904253675, 'rougeLsum': 0.6438336053077185} | {'score': 63.562323751931785, 'char_order': 6, 'word_order': 0, 'beta': 2} |


### Framework versions

- PEFT 0.7.2.dev0
- Transformers 4.36.1
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.15.0