---
library_name: transformers
license: apache-2.0
base_model: facebook/bart-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-base-aeslc-10-cnt-supervised-basic
  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. -->

# bart-base-aeslc-10-cnt-supervised-basic

This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 5.2943
- Rouge1: 0.1696
- Rouge2: 0.0823
- Rougel: 0.1631
- Rougelsum: 0.1636

## 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: 1e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 20

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 5.7302        | 1.6667  | 5    | 7.1464          | 0.158  | 0.0706 | 0.1462 | 0.1466    |
| 4.8072        | 3.3333  | 10   | 6.0947          | 0.1584 | 0.0706 | 0.1465 | 0.1471    |
| 3.458         | 5.0     | 15   | 5.3886          | 0.1584 | 0.0722 | 0.147  | 0.1476    |
| 2.8224        | 6.6667  | 20   | 5.1206          | 0.1532 | 0.071  | 0.144  | 0.1442    |
| 2.6376        | 8.3333  | 25   | 5.0738          | 0.1528 | 0.0755 | 0.1456 | 0.1455    |
| 2.3504        | 10.0    | 30   | 5.1150          | 0.1486 | 0.0748 | 0.1437 | 0.1438    |
| 1.7316        | 11.6667 | 35   | 5.1763          | 0.1515 | 0.0754 | 0.1465 | 0.1465    |
| 1.7152        | 13.3333 | 40   | 5.2225          | 0.1563 | 0.0768 | 0.1509 | 0.1511    |
| 1.5365        | 15.0    | 45   | 5.2511          | 0.1657 | 0.0804 | 0.1597 | 0.1601    |
| 1.5521        | 16.6667 | 50   | 5.2756          | 0.1682 | 0.0807 | 0.1618 | 0.1621    |
| 1.2753        | 18.3333 | 55   | 5.2903          | 0.1691 | 0.0812 | 0.1625 | 0.163     |
| 1.4062        | 20.0    | 60   | 5.2943          | 0.1696 | 0.0823 | 0.1631 | 0.1636    |


### Framework versions

- Transformers 4.57.3
- Pytorch 2.9.1+cu128
- Datasets 3.6.0
- Tokenizers 0.22.1