---
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: 3.0952
- Rouge1: 49.4298
- Rouge2: 31.7193
- Rougel: 44.732
- Rougelsum: 44.9281

## 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  | 9.5151          | 8.9002  | 0.0056  | 8.9059  | 8.8991    |
| No log        | 2.0   | 380  | 1.7786          | 44.8765 | 27.9652 | 40.2081 | 40.3457   |
| 4.488         | 3.0   | 570  | 1.7104          | 46.4054 | 28.8582 | 41.6579 | 41.86     |
| 4.488         | 4.0   | 760  | 1.7601          | 47.6046 | 30.1854 | 42.9171 | 43.0745   |
| 1.1057        | 5.0   | 950  | 1.9232          | 48.1693 | 30.1535 | 43.0418 | 43.1796   |
| 1.1057        | 6.0   | 1140 | 2.2791          | 43.831  | 26.9216 | 39.1768 | 39.3672   |
| 1.1057        | 7.0   | 1330 | 2.4800          | 42.4614 | 25.2371 | 37.6735 | 37.9309   |
| 0.4401        | 8.0   | 1520 | 2.4991          | 46.6653 | 28.9836 | 42.1188 | 42.2492   |
| 0.4401        | 9.0   | 1710 | 2.5826          | 47.2784 | 29.8703 | 42.622  | 42.7514   |
| 0.2523        | 10.0  | 1900 | 2.6356          | 48.0382 | 30.8884 | 43.3523 | 43.5068   |
| 0.2523        | 11.0  | 2090 | 2.6141          | 47.6911 | 29.3254 | 42.4938 | 42.6519   |
| 0.2523        | 12.0  | 2280 | 2.6942          | 48.7597 | 30.9279 | 43.5391 | 43.6974   |
| 0.1613        | 13.0  | 2470 | 2.7194          | 49.0916 | 30.9767 | 43.9943 | 44.1572   |
| 0.1613        | 14.0  | 2660 | 2.7911          | 47.8223 | 30.6173 | 43.1809 | 43.3471   |
| 0.1305        | 15.0  | 2850 | 2.8370          | 47.5629 | 29.7783 | 42.7168 | 42.8503   |
| 0.1305        | 16.0  | 3040 | 2.8588          | 49.4762 | 31.6101 | 44.5422 | 44.7027   |
| 0.1305        | 17.0  | 3230 | 2.9082          | 49.1502 | 31.4654 | 44.2166 | 44.3186   |
| 0.141         | 18.0  | 3420 | 2.8887          | 48.9675 | 31.0485 | 44.177  | 44.3258   |
| 0.141         | 19.0  | 3610 | 2.9043          | 49.2936 | 31.5204 | 44.2215 | 44.4216   |
| 0.1096        | 20.0  | 3800 | 2.9549          | 48.0316 | 30.4505 | 42.9444 | 43.0893   |
| 0.1096        | 21.0  | 3990 | 2.9666          | 49.2276 | 31.2755 | 44.2435 | 44.4591   |
| 0.1096        | 22.0  | 4180 | 2.9697          | 49.1008 | 31.4931 | 44.1893 | 44.382    |
| 0.0773        | 23.0  | 4370 | 2.9970          | 49.3707 | 31.4672 | 44.6066 | 44.7685   |
| 0.0773        | 24.0  | 4560 | 3.0081          | 49.2172 | 31.4693 | 44.4235 | 44.5458   |
| 0.048         | 25.0  | 4750 | 2.9968          | 49.4847 | 31.8341 | 44.8464 | 45.0286   |
| 0.048         | 26.0  | 4940 | 3.0405          | 49.5724 | 31.612  | 44.5192 | 44.7717   |
| 0.048         | 27.0  | 5130 | 3.0651          | 49.0194 | 31.2473 | 44.177  | 44.3837   |
| 0.0274        | 28.0  | 5320 | 3.0740          | 49.2999 | 31.5672 | 44.56   | 44.8105   |
| 0.0274        | 29.0  | 5510 | 3.0842          | 49.2898 | 31.602  | 44.5414 | 44.754    |
| 0.0168        | 30.0  | 5700 | 3.0952          | 49.4298 | 31.7193 | 44.732  | 44.9281   |


### Framework versions

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