---
license: cc-by-nc-4.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: nllb-200-distilled-600M-finetuned_srimadbhagavatam_sns
  results: []
---

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# nllb-200-distilled-600M-finetuned_srimadbhagavatam_sns

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: 0.9632
- Rouge1: 39.9844
- Rouge2: 15.8187
- Rougel: 24.7601
- Rougelsum: 37.8611

## 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-05
- 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: 25

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 4.2029        | 1.0   | 193  | 3.5530          | 17.4525 | 1.8199  | 14.417  | 15.7939   |
| 3.6789        | 2.0   | 386  | 3.2385          | 18.4399 | 2.3063  | 14.4777 | 16.8663   |
| 3.4121        | 3.0   | 579  | 2.9913          | 18.6292 | 2.1671  | 14.0775 | 17.4039   |
| 3.1958        | 4.0   | 772  | 2.7935          | 20.9044 | 3.0869  | 15.7866 | 19.4597   |
| 3.0238        | 5.0   | 965  | 2.6154          | 22.9863 | 3.1733  | 15.4087 | 21.6705   |
| 2.8546        | 6.0   | 1158 | 2.4343          | 24.7063 | 4.0564  | 16.1424 | 23.2821   |
| 2.7           | 7.0   | 1351 | 2.2810          | 26.2011 | 4.6714  | 16.7887 | 24.6723   |
| 2.5532        | 8.0   | 1544 | 2.1071          | 30.7319 | 6.3718  | 17.4858 | 28.8254   |
| 2.42          | 9.0   | 1737 | 1.9742          | 28.5217 | 5.2919  | 16.9577 | 26.5686   |
| 2.2991        | 10.0  | 1930 | 1.8234          | 29.8937 | 6.3088  | 17.2141 | 28.0302   |
| 2.1851        | 11.0  | 2123 | 1.7177          | 29.8642 | 6.9874  | 18.2935 | 28.0493   |
| 2.0829        | 12.0  | 2316 | 1.5891          | 30.7551 | 6.7111  | 18.1772 | 28.8555   |
| 1.9954        | 13.0  | 2509 | 1.4965          | 32.6313 | 8.0662  | 18.4981 | 30.8014   |
| 1.9055        | 14.0  | 2702 | 1.3996          | 33.0299 | 9.6554  | 19.2763 | 31.2127   |
| 1.8372        | 15.0  | 2895 | 1.3271          | 35.4767 | 10.7234 | 20.2759 | 33.1856   |
| 1.7635        | 16.0  | 3088 | 1.2533          | 35.5164 | 11.5198 | 21.3301 | 33.2617   |
| 1.7052        | 17.0  | 3281 | 1.1865          | 37.5692 | 13.6047 | 22.9496 | 35.2626   |
| 1.6495        | 18.0  | 3474 | 1.1414          | 37.7493 | 13.6471 | 22.6947 | 35.6368   |
| 1.6009        | 19.0  | 3667 | 1.0859          | 40.251  | 15.2568 | 24.4602 | 37.955    |
| 1.5589        | 20.0  | 3860 | 1.0536          | 37.8875 | 14.5794 | 23.4696 | 35.8989   |
| 1.5209        | 21.0  | 4053 | 1.0268          | 38.4126 | 14.9535 | 24.3597 | 36.435    |
| 1.4963        | 22.0  | 4246 | 0.9982          | 40.9518 | 16.6418 | 25.284  | 38.5787   |
| 1.4651        | 23.0  | 4439 | 0.9771          | 39.4774 | 16.4189 | 24.7979 | 37.3614   |
| 1.451         | 24.0  | 4632 | 0.9662          | 40.4131 | 16.5895 | 25.0073 | 38.3018   |
| 1.4351        | 25.0  | 4825 | 0.9632          | 39.9844 | 15.8187 | 24.7601 | 37.8611   |


### Framework versions

- Transformers 4.28.0
- Pytorch 1.12.1
- Datasets 2.14.4
- Tokenizers 0.13.3