|
|
--- |
|
|
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 |
|
|
|
