---
library_name: transformers
license: apache-2.0
base_model: facebook/bart-large
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-large-aeslc-100-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-large-aeslc-100-cnt-supervised-basic

This model is a fine-tuned version of [facebook/bart-large](https://huggingface.co/facebook/bart-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 5.9904
- Rouge1: 0.2974
- Rouge2: 0.1434
- Rougel: 0.2907
- Rougelsum: 0.2902

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 5.1764        | 0.4   | 10   | 5.6551          | 0.1489 | 0.0635 | 0.1375 | 0.1374    |
| 3.9597        | 0.8   | 20   | 5.1629          | 0.2459 | 0.1214 | 0.2437 | 0.2436    |
| 3.4396        | 1.2   | 30   | 4.9109          | 0.293  | 0.146  | 0.2814 | 0.2812    |
| 3.0038        | 1.6   | 40   | 4.9415          | 0.2924 | 0.1489 | 0.2824 | 0.2822    |
| 2.8195        | 2.0   | 50   | 5.0323          | 0.2804 | 0.1449 | 0.2771 | 0.277     |
| 2.6185        | 2.4   | 60   | 4.9905          | 0.3058 | 0.1559 | 0.2963 | 0.2963    |
| 2.2683        | 2.8   | 70   | 5.0726          | 0.2994 | 0.1529 | 0.2923 | 0.292     |
| 2.1857        | 3.2   | 80   | 5.1591          | 0.2903 | 0.1441 | 0.2862 | 0.286     |
| 2.0587        | 3.6   | 90   | 5.1690          | 0.2985 | 0.1485 | 0.2912 | 0.2912    |
| 2.28          | 4.0   | 100  | 5.2317          | 0.3034 | 0.1508 | 0.2961 | 0.2961    |
| 1.7853        | 4.4   | 110  | 5.4102          | 0.2944 | 0.1462 | 0.2878 | 0.2877    |
| 1.9434        | 4.8   | 120  | 5.4227          | 0.3065 | 0.1529 | 0.3004 | 0.3       |
| 1.4693        | 5.2   | 130  | 5.4791          | 0.3053 | 0.1489 | 0.2984 | 0.2978    |
| 1.6331        | 5.6   | 140  | 5.5514          | 0.2964 | 0.1423 | 0.2906 | 0.2904    |
| 1.585         | 6.0   | 150  | 5.5008          | 0.2967 | 0.1436 | 0.2912 | 0.291     |
| 1.3414        | 6.4   | 160  | 5.5670          | 0.2981 | 0.147  | 0.2919 | 0.2917    |
| 1.2337        | 6.8   | 170  | 5.6861          | 0.2973 | 0.1471 | 0.2916 | 0.2911    |
| 1.1571        | 7.2   | 180  | 5.8000          | 0.2914 | 0.1401 | 0.2856 | 0.2854    |
| 1.6853        | 7.6   | 190  | 5.9097          | 0.2922 | 0.1406 | 0.2862 | 0.2861    |
| 1.0714        | 8.0   | 200  | 5.9439          | 0.2954 | 0.143  | 0.2884 | 0.2883    |
| 0.9668        | 8.4   | 210  | 5.9412          | 0.2975 | 0.1449 | 0.2905 | 0.2904    |
| 1.0741        | 8.8   | 220  | 5.9350          | 0.2989 | 0.1436 | 0.292  | 0.2918    |
| 1.0771        | 9.2   | 230  | 5.9855          | 0.2954 | 0.1425 | 0.2887 | 0.2883    |
| 0.96          | 9.6   | 240  | 5.9881          | 0.297  | 0.1435 | 0.2903 | 0.29      |
| 1.0673        | 10.0  | 250  | 5.9904          | 0.2974 | 0.1434 | 0.2907 | 0.2902    |


### Framework versions

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