---
tags:
- simplification
- generated_from_trainer
metrics:
- rouge
model-index:
- name: NASES-clara-med
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# NASES-clara-med

This model is a fine-tuned version of [ELiRF/NASES](https://huggingface.co/ELiRF/NASES) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.1300
- Rouge1: 45.8234
- Rouge2: 27.9023
- Rougel: 40.0601
- Rougelsum: 40.1365

## 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  | 2.1020          | 44.2638 | 26.5513 | 38.8656 | 38.9574   |
| No log        | 2.0   | 380  | 2.0341          | 44.8083 | 27.3491 | 39.2192 | 39.2873   |
| 1.8386        | 3.0   | 570  | 2.0883          | 44.9818 | 27.5372 | 39.702  | 39.7941   |
| 1.8386        | 4.0   | 760  | 2.1829          | 45.3864 | 28.2511 | 40.224  | 40.3422   |
| 0.6628        | 5.0   | 950  | 2.3020          | 45.1704 | 27.6203 | 39.6343 | 39.8564   |
| 0.6628        | 6.0   | 1140 | 2.3936          | 45.245  | 27.5998 | 39.5014 | 39.7109   |
| 0.6628        | 7.0   | 1330 | 2.5143          | 45.419  | 27.8554 | 39.7599 | 39.8859   |
| 0.2204        | 8.0   | 1520 | 2.5889          | 45.3461 | 27.8309 | 39.7638 | 39.7984   |
| 0.2204        | 9.0   | 1710 | 2.6406          | 45.0848 | 27.6269 | 39.499  | 39.5797   |
| 0.1278        | 10.0  | 1900 | 2.6651          | 44.8955 | 27.1523 | 39.0341 | 39.1819   |
| 0.1278        | 11.0  | 2090 | 2.7188          | 44.8196 | 27.3935 | 39.1979 | 39.2786   |
| 0.1278        | 12.0  | 2280 | 2.7608          | 45.3321 | 27.7995 | 39.755  | 39.8835   |
| 0.0849        | 13.0  | 2470 | 2.7928          | 45.3633 | 27.7144 | 39.7197 | 39.8112   |
| 0.0849        | 14.0  | 2660 | 2.8243          | 45.2905 | 27.8178 | 39.8823 | 39.9496   |
| 0.0655        | 15.0  | 2850 | 2.8515          | 45.8272 | 28.2161 | 40.2645 | 40.3717   |
| 0.0655        | 16.0  | 3040 | 2.8778          | 45.4863 | 27.8831 | 39.7118 | 39.7972   |
| 0.0655        | 17.0  | 3230 | 2.9078          | 45.3699 | 27.8244 | 39.5926 | 39.6862   |
| 0.0515        | 18.0  | 3420 | 2.9201          | 45.601  | 28.0129 | 40.0033 | 40.085    |
| 0.0515        | 19.0  | 3610 | 2.9525          | 45.6083 | 27.8189 | 39.8085 | 39.9177   |
| 0.0427        | 20.0  | 3800 | 2.9935          | 45.3061 | 27.2807 | 39.3424 | 39.4389   |
| 0.0427        | 21.0  | 3990 | 3.0076          | 45.2374 | 27.337  | 39.5316 | 39.5977   |
| 0.0427        | 22.0  | 4180 | 3.0457          | 46.1103 | 27.8833 | 40.1059 | 40.1985   |
| 0.0272        | 23.0  | 4370 | 3.0433          | 45.4395 | 27.8712 | 40.001  | 40.0459   |
| 0.0272        | 24.0  | 4560 | 3.0483          | 45.6994 | 27.6396 | 39.8601 | 39.9617   |
| 0.0188        | 25.0  | 4750 | 3.0561          | 45.7877 | 27.808  | 40.1369 | 40.1748   |
| 0.0188        | 26.0  | 4940 | 3.0849          | 45.574  | 27.6999 | 39.8785 | 39.9602   |
| 0.0188        | 27.0  | 5130 | 3.1076          | 45.7393 | 27.8011 | 39.9347 | 39.9889   |
| 0.0149        | 28.0  | 5320 | 3.1277          | 45.6849 | 27.6962 | 39.85   | 39.9121   |
| 0.0149        | 29.0  | 5510 | 3.1181          | 45.8135 | 27.7591 | 39.9626 | 39.9888   |
| 0.0119        | 30.0  | 5700 | 3.1300          | 45.8234 | 27.9023 | 40.0601 | 40.1365   |


### Framework versions

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