---
tags:
- summarization
- generated_from_trainer
model-index:
- name: NAS-bilingue
  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. -->

# NAS-bilingue

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.7187
- Rougelsum: 0.0922

## 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: 1.3739167643078955e-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:---------:|
| No log        | 1.0   | 5    | 4.5936          | 0.0759    |
| No log        | 2.0   | 10   | 4.4276          | 0.0759    |
| No log        | 3.0   | 15   | 4.2936          | 0.0759    |
| No log        | 4.0   | 20   | 4.1820          | 0.0759    |
| No log        | 5.0   | 25   | 4.0896          | 0.0881    |
| No log        | 6.0   | 30   | 4.0121          | 0.0970    |
| No log        | 7.0   | 35   | 3.9451          | 0.0918    |
| No log        | 8.0   | 40   | 3.8875          | 0.0922    |
| No log        | 9.0   | 45   | 3.8395          | 0.0922    |
| No log        | 10.0  | 50   | 3.8011          | 0.0922    |
| No log        | 11.0  | 55   | 3.7707          | 0.0922    |
| No log        | 12.0  | 60   | 3.7480          | 0.0922    |
| No log        | 13.0  | 65   | 3.7320          | 0.0922    |
| No log        | 14.0  | 70   | 3.7223          | 0.0922    |
| No log        | 15.0  | 75   | 3.7187          | 0.0922    |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.9.0
- Tokenizers 0.13.2