---
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_lexrank
  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_lexrank

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: 3.8356
- Rouge1: 15.0234
- Rouge2: 1.2752
- Rougel: 12.4341
- Rougelsum: 13.036

## 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: 5
- eval_batch_size: 5
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 4.9309        | 1.0   | 86   | 4.4877          | 17.9643 | 1.8368 | 13.627  | 16.743    |
| 4.5531        | 2.0   | 172  | 4.2961          | 7.7741  | 0.7819 | 6.5664  | 7.0319    |
| 4.4082        | 3.0   | 258  | 4.1867          | 15.3171 | 1.2616 | 12.5029 | 13.4603   |
| 4.3142        | 4.0   | 344  | 4.1128          | 14.7478 | 1.299  | 12.4545 | 12.8832   |
| 4.22          | 5.0   | 430  | 4.0577          | 14.6397 | 1.1974 | 12.3644 | 12.5395   |
| 4.1743        | 6.0   | 516  | 4.0173          | 14.7595 | 1.3556 | 12.4877 | 12.6788   |
| 4.1279        | 7.0   | 602  | 3.9858          | 14.3561 | 1.3361 | 12.071  | 12.5251   |
| 4.0927        | 8.0   | 688  | 3.9564          | 15.0213 | 1.3697 | 12.7109 | 13.1084   |
| 4.0625        | 9.0   | 774  | 3.9320          | 15.2813 | 1.3317 | 12.635  | 13.4154   |
| 4.0361        | 10.0  | 860  | 3.9113          | 15.0786 | 1.2544 | 12.6139 | 13.0141   |
| 3.9913        | 11.0  | 946  | 3.8951          | 15.0242 | 1.2899 | 12.7049 | 13.1678   |
| 3.9949        | 12.0  | 1032 | 3.8822          | 15.1567 | 1.3332 | 12.7349 | 13.1691   |
| 3.9643        | 13.0  | 1118 | 3.8724          | 15.0434 | 1.2552 | 12.6509 | 13.1845   |
| 3.96          | 14.0  | 1204 | 3.8608          | 14.5834 | 1.2768 | 12.1898 | 12.5734   |
| 3.9524        | 15.0  | 1290 | 3.8533          | 14.6872 | 1.2161 | 12.2549 | 12.7557   |
| 3.9345        | 16.0  | 1376 | 3.8443          | 15.0962 | 1.3235 | 12.5689 | 13.1217   |
| 3.9359        | 17.0  | 1462 | 3.8407          | 14.7724 | 1.2323 | 12.4059 | 12.6775   |
| 3.9213        | 18.0  | 1548 | 3.8367          | 14.6599 | 1.285  | 12.2237 | 12.7231   |
| 3.9213        | 19.0  | 1634 | 3.8356          | 15.0234 | 1.2752 | 12.4341 | 13.036    |


### Framework versions

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