---
license: cc-by-nc-4.0
library_name: peft
tags:
- generated_from_trainer
base_model: facebook/nllb-200-distilled-1.3B
metrics:
- bleu
- rouge
model-index:
- name: nllb-200-distilled-1.3B-ICFOSS-Malayalam_Tamil_Translation1
  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-ICFOSS-Malayalam_Tamil_Translation1

This model is a fine-tuned version of [facebook/nllb-200-distilled-1.3B](https://huggingface.co/facebook/nllb-200-distilled-1.3B) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9585
- Bleu: 27.2186
- Rouge: {'rouge1': 0.24019241472720237, 'rouge2': 0.11743746052802109, 'rougeL': 0.23538895581779812, 'rougeLsum': 0.23566947893424423}
- Chrf: {'score': 61.354962127257075, '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: 16
- eval_batch_size: 16
- 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                                                                       |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------------------------------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------:|
| 1.0887        | 1.0   | 3200  | 0.9812          | 26.4453 | {'rouge1': 0.23999162519568762, 'rouge2': 0.11750820308459373, 'rougeL': 0.2354759340604931, 'rougeLsum': 0.23574425317949493}  | {'score': 60.78556495445389, 'char_order': 6, 'word_order': 0, 'beta': 2}  |
| 1.0235        | 2.0   | 6400  | 0.9633          | 27.2057 | {'rouge1': 0.23965959444048868, 'rouge2': 0.11732010332857629, 'rougeL': 0.2348755068042092, 'rougeLsum': 0.2350956429627365}   | {'score': 61.143671039500624, 'char_order': 6, 'word_order': 0, 'beta': 2} |
| 1.0073        | 3.0   | 9600  | 0.9592          | 27.2471 | {'rouge1': 0.24051300083618463, 'rouge2': 0.11760625620421375, 'rougeL': 0.23594757428338253, 'rougeLsum': 0.23612557860955713} | {'score': 61.30740344086827, 'char_order': 6, 'word_order': 0, 'beta': 2}  |
| 1.0022        | 4.0   | 12800 | 0.9587          | 27.2024 | {'rouge1': 0.24037345843038344, 'rouge2': 0.1174835459617575, 'rougeL': 0.2356757544571015, 'rougeLsum': 0.23591228047430784}   | {'score': 61.34302070824752, 'char_order': 6, 'word_order': 0, 'beta': 2}  |
| 1.0008        | 5.0   | 16000 | 0.9585          | 27.2186 | {'rouge1': 0.24019241472720237, 'rouge2': 0.11743746052802109, 'rougeL': 0.23538895581779812, 'rougeLsum': 0.23566947893424423} | {'score': 61.354962127257075, 'char_order': 6, 'word_order': 0, 'beta': 2} |


### Framework versions

- PEFT 0.10.0
- Transformers 4.39.3
- Pytorch 2.1.0+cu121
- Datasets 2.19.0
- Tokenizers 0.15.0