---
license: cc-by-nc-4.0
base_model: facebook/nllb-200-distilled-600M
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: nllb-200-distilled-600M-finetuned_ramayana_sns_prose
  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-600M-finetuned_ramayana_sns_prose

This model is a fine-tuned version of [facebook/nllb-200-distilled-600M](https://huggingface.co/facebook/nllb-200-distilled-600M) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.5584
- Rouge1: 19.8304
- Rouge2: 2.4248
- Rougel: 13.9446
- Rougelsum: 18.3552

## 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: 5.6e-06
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 4.595         | 1.0   | 427  | 4.1428          | 15.776  | 1.4778 | 12.3256 | 14.3476   |
| 4.1875        | 2.0   | 854  | 3.9597          | 16.6403 | 1.7896 | 12.7134 | 15.0805   |
| 4.0304        | 3.0   | 1281 | 3.8653          | 16.6812 | 1.8152 | 12.5282 | 15.1217   |
| 3.9243        | 4.0   | 1708 | 3.7984          | 17.1533 | 1.788  | 13.1478 | 15.5023   |
| 3.8485        | 5.0   | 2135 | 3.7505          | 17.3886 | 1.8682 | 13.1805 | 15.711    |
| 3.786         | 6.0   | 2562 | 3.7141          | 17.7897 | 1.9953 | 13.2044 | 15.9314   |
| 3.732         | 7.0   | 2989 | 3.6815          | 18.3797 | 2.0735 | 13.8603 | 16.7243   |
| 3.6865        | 8.0   | 3416 | 3.6559          | 18.2702 | 2.0286 | 13.3494 | 16.5957   |
| 3.6515        | 9.0   | 3843 | 3.6354          | 18.0194 | 1.9282 | 12.9295 | 16.4714   |
| 3.6177        | 10.0  | 4270 | 3.6193          | 18.7825 | 2.0085 | 13.2207 | 17.1223   |
| 3.5877        | 11.0  | 4697 | 3.6030          | 19.1192 | 2.1276 | 13.9442 | 17.609    |
| 3.5665        | 12.0  | 5124 | 3.5943          | 19.5031 | 2.3146 | 13.7631 | 17.9879   |
| 3.5454        | 13.0  | 5551 | 3.5828          | 19.7688 | 2.2574 | 13.9943 | 18.2914   |
| 3.5247        | 14.0  | 5978 | 3.5763          | 19.4478 | 2.3024 | 13.8854 | 17.9616   |
| 3.509         | 15.0  | 6405 | 3.5704          | 19.3998 | 2.2633 | 13.707  | 17.9534   |
| 3.4983        | 16.0  | 6832 | 3.5646          | 19.6401 | 2.3265 | 13.9141 | 18.2001   |
| 3.4865        | 17.0  | 7259 | 3.5604          | 19.1833 | 2.398  | 13.6566 | 17.7596   |
| 3.4802        | 18.0  | 7686 | 3.5584          | 19.8304 | 2.4248 | 13.9446 | 18.3552   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.0.1+cu117
- Datasets 2.19.2
- Tokenizers 0.19.1