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---
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
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