---
tags:
- simplification
- generated_from_trainer
metrics:
- rouge
model-index:
- name: marimari-r2r-mlsum-clara-med
  results: []
---

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# marimari-r2r-mlsum-clara-med

This model is a fine-tuned version of [IIC/marimari-r2r-mlsum](https://huggingface.co/IIC/marimari-r2r-mlsum) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 4.0687
- Rouge1: 41.588
- Rouge2: 23.5096
- Rougel: 35.9281
- Rougelsum: 36.128

## 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  | 2.3804          | 41.7652 | 24.3329 | 36.7515 | 36.8694   |
| No log        | 2.0   | 380  | 2.3417          | 41.586  | 23.679  | 35.8653 | 36.065    |
| 1.9588        | 3.0   | 570  | 2.4777          | 40.954  | 23.0312 | 35.4667 | 35.7321   |
| 1.9588        | 4.0   | 760  | 2.8230          | 41.387  | 23.4641 | 35.9558 | 36.1302   |
| 0.6288        | 5.0   | 950  | 3.0836          | 40.7233 | 22.4476 | 34.852  | 35.1656   |
| 0.6288        | 6.0   | 1140 | 3.2078          | 40.8334 | 22.4327 | 35.0436 | 35.2623   |
| 0.6288        | 7.0   | 1330 | 3.3649          | 40.6737 | 22.4294 | 34.5433 | 34.9343   |
| 0.1473        | 8.0   | 1520 | 3.4503          | 40.8818 | 22.6808 | 34.6777 | 34.9179   |
| 0.1473        | 9.0   | 1710 | 3.5140          | 40.4208 | 22.2582 | 34.5103 | 34.8161   |
| 0.0706        | 10.0  | 1900 | 3.5805          | 40.6348 | 22.4714 | 34.6782 | 34.9531   |
| 0.0706        | 11.0  | 2090 | 3.6325          | 40.932  | 22.4958 | 34.7695 | 35.0314   |
| 0.0706        | 12.0  | 2280 | 3.6405          | 40.619  | 22.406  | 34.9997 | 35.3007   |
| 0.0401        | 13.0  | 2470 | 3.7279          | 40.7365 | 22.2549 | 34.6789 | 34.9794   |
| 0.0401        | 14.0  | 2660 | 3.7440          | 41.1684 | 23.1526 | 35.4117 | 35.7039   |
| 0.0277        | 15.0  | 2850 | 3.8185          | 41.3103 | 23.52   | 35.5945 | 35.9176   |
| 0.0277        | 16.0  | 3040 | 3.8215          | 40.5096 | 22.3435 | 34.7064 | 35.0037   |
| 0.0277        | 17.0  | 3230 | 3.8925          | 41.3644 | 23.2827 | 35.3861 | 35.6649   |
| 0.0172        | 18.0  | 3420 | 3.8594          | 41.6572 | 23.574  | 35.5946 | 35.8383   |
| 0.0172        | 19.0  | 3610 | 3.9191          | 41.4862 | 23.2408 | 35.5638 | 35.7895   |
| 0.0087        | 20.0  | 3800 | 3.8776          | 41.8812 | 23.6052 | 35.9983 | 36.2555   |
| 0.0087        | 21.0  | 3990 | 3.9526          | 42.0435 | 23.6758 | 36.0881 | 36.3736   |
| 0.0087        | 22.0  | 4180 | 3.9847          | 41.7187 | 23.5729 | 36.0514 | 36.3019   |
| 0.0036        | 23.0  | 4370 | 3.9939          | 41.6098 | 23.3451 | 35.779  | 35.9889   |
| 0.0036        | 24.0  | 4560 | 4.0194          | 41.1443 | 23.1271 | 35.6529 | 35.808    |
| 0.002         | 25.0  | 4750 | 4.0231          | 41.5422 | 23.5603 | 35.8412 | 36.0677   |
| 0.002         | 26.0  | 4940 | 4.0439          | 41.5561 | 23.5496 | 35.8154 | 36.0846   |
| 0.002         | 27.0  | 5130 | 4.0554          | 41.6566 | 23.4052 | 35.8392 | 36.0672   |
| 0.0014        | 28.0  | 5320 | 4.0610          | 41.6654 | 23.5138 | 35.9715 | 36.1973   |
| 0.0014        | 29.0  | 5510 | 4.0658          | 41.5467 | 23.464  | 35.7852 | 36.0226   |
| 0.0011        | 30.0  | 5700 | 4.0687          | 41.588  | 23.5096 | 35.9281 | 36.128    |


### Framework versions

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