---
license: apache-2.0
base_model: sshleifer/distilbart-xsum-12-6
tags:
- generated_from_trainer
model-index:
- name: bart-abs-2409-0144-lr-3e-05-bs-4-maxep-10
  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-abs-2409-0144-lr-3e-05-bs-4-maxep-10

This model is a fine-tuned version of [sshleifer/distilbart-xsum-12-6](https://huggingface.co/sshleifer/distilbart-xsum-12-6) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.7398
- Rouge/rouge1: 0.4519
- Rouge/rouge2: 0.1957
- Rouge/rougel: 0.3795
- Rouge/rougelsum: 0.3809
- Bertscore/bertscore-precision: 0.8939
- Bertscore/bertscore-recall: 0.8913
- Bertscore/bertscore-f1: 0.8925
- Meteor: 0.4012
- Gen Len: 37.1455

## 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: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge/rouge1 | Rouge/rouge2 | Rouge/rougel | Rouge/rougelsum | Bertscore/bertscore-precision | Bertscore/bertscore-recall | Bertscore/bertscore-f1 | Meteor | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------------:|:------------:|:------------:|:---------------:|:-----------------------------:|:--------------------------:|:----------------------:|:------:|:-------:|
| 0.7649        | 1.0   | 217  | 2.3871          | 0.4493       | 0.2047       | 0.3867       | 0.3879          | 0.8969                        | 0.89                       | 0.8933                 | 0.3916 | 35.6364 |
| 0.5599        | 2.0   | 434  | 2.5775          | 0.4553       | 0.2005       | 0.3849       | 0.3861          | 0.8951                        | 0.8914                     | 0.8931                 | 0.3951 | 36.1636 |
| 0.4078        | 3.0   | 651  | 2.9176          | 0.4622       | 0.2118       | 0.3904       | 0.3927          | 0.8942                        | 0.8925                     | 0.8932                 | 0.4137 | 36.9818 |
| 0.2969        | 4.0   | 868  | 3.1512          | 0.4589       | 0.2038       | 0.3877       | 0.3892          | 0.8957                        | 0.8886                     | 0.892                  | 0.3961 | 34.6364 |
| 0.2291        | 5.0   | 1085 | 3.3475          | 0.4594       | 0.2035       | 0.3899       | 0.3915          | 0.8964                        | 0.8925                     | 0.8943                 | 0.4099 | 36.9364 |
| 0.2006        | 6.0   | 1302 | 3.3661          | 0.466        | 0.209        | 0.3934       | 0.3959          | 0.896                         | 0.8933                     | 0.8945                 | 0.4136 | 37.2818 |
| 0.1485        | 7.0   | 1519 | 3.5165          | 0.4639       | 0.2054       | 0.3846       | 0.3862          | 0.8939                        | 0.8931                     | 0.8934                 | 0.4137 | 38.7636 |
| 0.1131        | 8.0   | 1736 | 3.6478          | 0.4595       | 0.202        | 0.3882       | 0.3908          | 0.8958                        | 0.8903                     | 0.8929                 | 0.402  | 35.2727 |
| 0.0945        | 9.0   | 1953 | 3.7024          | 0.4614       | 0.2048       | 0.39         | 0.391           | 0.8933                        | 0.894                      | 0.8935                 | 0.4163 | 40.1545 |
| 0.0794        | 10.0  | 2170 | 3.7398          | 0.4519       | 0.1957       | 0.3795       | 0.3809          | 0.8939                        | 0.8913                     | 0.8925                 | 0.4012 | 37.1455 |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1