---
license: mit
tags:
- simplification
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mbart-large-50-clara-med
  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. -->

# mbart-large-50-clara-med

This model is a fine-tuned version of [facebook/mbart-large-50](https://huggingface.co/facebook/mbart-large-50) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.2175
- Rouge1: 48.3311
- Rouge2: 30.5638
- Rougel: 43.5214
- Rougelsum: 43.6488

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| No log        | 1.0   | 190  | 3.2394          | 16.8539 | 2.7013  | 12.425  | 12.5286   |
| No log        | 2.0   | 380  | 1.7381          | 44.5316 | 27.8022 | 40.1591 | 40.3177   |
| 3.4249        | 3.0   | 570  | 1.7198          | 45.6463 | 28.6925 | 41.263  | 41.4703   |
| 3.4249        | 4.0   | 760  | 1.9450          | 43.0233 | 26.3397 | 38.7518 | 38.9154   |
| 0.8377        | 5.0   | 950  | 2.1068          | 46.5936 | 28.7218 | 41.7184 | 41.8448   |
| 0.8377        | 6.0   | 1140 | 2.2815          | 46.4517 | 28.5639 | 41.8107 | 41.9996   |
| 0.8377        | 7.0   | 1330 | 2.4726          | 46.0403 | 28.1887 | 40.9183 | 41.0318   |
| 0.3195        | 8.0   | 1520 | 2.5690          | 47.255  | 29.1482 | 42.4463 | 42.5728   |
| 0.3195        | 9.0   | 1710 | 2.6753          | 46.5967 | 28.5688 | 41.414  | 41.5889   |
| 0.1925        | 10.0  | 1900 | 2.7276          | 46.3251 | 28.4889 | 41.4556 | 41.581    |
| 0.1925        | 11.0  | 2090 | 2.7638          | 46.9325 | 29.2558 | 41.726  | 41.8413   |
| 0.1925        | 12.0  | 2280 | 2.8273          | 47.0344 | 29.1298 | 41.7291 | 41.9236   |
| 0.1313        | 13.0  | 2470 | 2.8633          | 47.5234 | 29.6376 | 42.3409 | 42.4372   |
| 0.1313        | 14.0  | 2660 | 2.8989          | 47.0396 | 29.117  | 41.9893 | 42.1846   |
| 0.1117        | 15.0  | 2850 | 2.9691          | 47.8406 | 29.889  | 42.5645 | 42.7676   |
| 0.1117        | 16.0  | 3040 | 2.9763          | 46.9489 | 28.9919 | 41.8404 | 42.0141   |
| 0.1117        | 17.0  | 3230 | 2.9985          | 47.6628 | 29.7341 | 42.6382 | 42.7649   |
| 0.0824        | 18.0  | 3420 | 3.0511          | 48.0627 | 30.4108 | 43.1693 | 43.3489   |
| 0.0824        | 19.0  | 3610 | 3.0102          | 48.05   | 29.9552 | 43.1462 | 43.3421   |
| 0.0467        | 20.0  | 3800 | 3.0520          | 47.5451 | 29.6129 | 42.6499 | 42.7968   |
| 0.0467        | 21.0  | 3990 | 3.0978          | 47.5042 | 29.6191 | 42.6093 | 42.7341   |
| 0.0467        | 22.0  | 4180 | 3.1270          | 47.8301 | 29.9484 | 42.6866 | 42.9179   |
| 0.0246        | 23.0  | 4370 | 3.1435          | 47.6683 | 30.1974 | 43.0456 | 43.1496   |
| 0.0246        | 24.0  | 4560 | 3.1599          | 47.8652 | 30.2751 | 43.0445 | 43.1898   |
| 0.013         | 25.0  | 4750 | 3.1750          | 48.1352 | 30.4185 | 43.0485 | 43.2456   |
| 0.013         | 26.0  | 4940 | 3.1939          | 47.9653 | 30.3968 | 43.1271 | 43.2522   |
| 0.013         | 27.0  | 5130 | 3.2054          | 48.2122 | 30.6    | 43.3461 | 43.4629   |
| 0.0071        | 28.0  | 5320 | 3.1964          | 47.924  | 30.3089 | 43.0402 | 43.2016   |
| 0.0071        | 29.0  | 5510 | 3.2123          | 48.2967 | 30.5088 | 43.431  | 43.5384   |
| 0.005         | 30.0  | 5700 | 3.2175          | 48.3311 | 30.5638 | 43.5214 | 43.6488   |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.0
- Datasets 2.8.0
- Tokenizers 0.12.1