---
library_name: transformers
license: apache-2.0
base_model: facebook/bart-large
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-large-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-large-aeslc-10-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: 5.5122
- Rouge1: 0.2421
- Rouge2: 0.1162
- Rougel: 0.23
- Rougelsum: 0.2305

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 4.8115        | 2.5   | 5    | 5.6510          | 0.1512 | 0.0659 | 0.1397 | 0.1397    |
| 2.9123        | 5.0   | 10   | 4.9927          | 0.232  | 0.1171 | 0.2223 | 0.2229    |
| 1.4885        | 7.5   | 15   | 5.0836          | 0.2577 | 0.1312 | 0.2487 | 0.2493    |
| 1.2593        | 10.0  | 20   | 5.1864          | 0.2555 | 0.1244 | 0.2435 | 0.244     |
| 0.9244        | 12.5  | 25   | 5.3341          | 0.2493 | 0.1196 | 0.2361 | 0.2364    |
| 0.8451        | 15.0  | 30   | 5.4642          | 0.2438 | 0.1175 | 0.2315 | 0.2318    |
| 0.9148        | 17.5  | 35   | 5.5031          | 0.2433 | 0.1167 | 0.2313 | 0.2316    |
| 0.6394        | 20.0  | 40   | 5.5122          | 0.2421 | 0.1162 | 0.23   | 0.2305    |


### Framework versions

- Transformers 4.53.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.2