---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- aeslc
metrics:
- rouge
model-index:
- name: bart-large-finetuned-aeslc
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: aeslc
      type: aeslc
      config: default
      split: validation
      args: default
    metrics:
    - name: Rouge1
      type: rouge
      value: 38.0679
---

<!-- 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-finetuned-aeslc

This model is a fine-tuned version of [facebook/bart-large](https://huggingface.co/facebook/bart-large) on the aeslc dataset.
It achieves the following results on the evaluation set:
- Loss: 4.6657
- Rouge1: 38.0679
- Rouge2: 19.8904
- Rougel: 37.1179
- Rougelsum: 37.1066
- Gen Len: 9.1316

## 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: 2e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 2.6268        | 1.0   | 7218  | 4.4738          | 36.0615 | 18.1082 | 35.2023 | 35.175    | 8.0694  |
| 1.9548        | 2.0   | 14436 | 4.4965          | 37.1784 | 19.2713 | 36.2803 | 36.2347   | 9.2699  |
| 1.4117        | 3.0   | 21654 | 4.6657          | 38.0679 | 19.8904 | 37.1179 | 37.1066   | 9.1316  |


### Framework versions

- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3