---
license: apache-2.0
base_model: sshleifer/distilbart-xsum-12-6
tags:
- generated_from_trainer
model-index:
- name: bart-abs-1509-0313-lr-0.0003-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-1509-0313-lr-0.0003-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: 4.7482
- Rouge/rouge1: 0.4015
- Rouge/rouge2: 0.1493
- Rouge/rougel: 0.329
- Rouge/rougelsum: 0.3294
- Bertscore/bertscore-precision: 0.8894
- Bertscore/bertscore-recall: 0.8807
- Bertscore/bertscore-f1: 0.8849
- Meteor: 0.3397
- Gen Len: 33.2

## 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: 0.0003
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------------:|:------------:|:------------:|:---------------:|:-----------------------------:|:--------------------------:|:----------------------:|:------:|:-------:|
| 1.722         | 1.0   | 217  | 2.6756          | 0.4274       | 0.1866       | 0.3588       | 0.3592          | 0.8936                        | 0.884                      | 0.8886                 | 0.3527 | 32.9545 |
| 1.7652        | 2.0   | 434  | 2.7321          | 0.416        | 0.1726       | 0.3511       | 0.3521          | 0.8944                        | 0.8818                     | 0.888                  | 0.3352 | 31.5909 |
| 1.135         | 3.0   | 651  | 2.9372          | 0.3752       | 0.1441       | 0.3163       | 0.3158          | 0.8968                        | 0.8736                     | 0.8849                 | 0.2976 | 26.4    |
| 0.9762        | 4.0   | 868  | 3.1311          | 0.3959       | 0.1535       | 0.3344       | 0.3353          | 0.8893                        | 0.8777                     | 0.8833                 | 0.3296 | 33.1273 |
| 0.7207        | 5.0   | 1085 | 3.3741          | 0.4028       | 0.1562       | 0.3388       | 0.3389          | 0.8889                        | 0.8818                     | 0.8852                 | 0.3324 | 34.3273 |
| 0.3986        | 6.0   | 1302 | 3.4504          | 0.4245       | 0.1689       | 0.3493       | 0.3501          | 0.892                         | 0.8834                     | 0.8876                 | 0.351  | 34.4727 |
| 0.2471        | 7.0   | 1519 | 3.8316          | 0.4096       | 0.1536       | 0.3384       | 0.3389          | 0.8922                        | 0.8814                     | 0.8867                 | 0.3376 | 32.7909 |
| 0.1613        | 8.0   | 1736 | 4.2439          | 0.4201       | 0.1621       | 0.346        | 0.347           | 0.8921                        | 0.8815                     | 0.8866                 | 0.3503 | 33.3    |
| 0.0989        | 9.0   | 1953 | 4.4784          | 0.4115       | 0.1499       | 0.3394       | 0.3408          | 0.8904                        | 0.8825                     | 0.8863                 | 0.3409 | 34.0    |
| 0.0644        | 10.0  | 2170 | 4.7482          | 0.4015       | 0.1493       | 0.329        | 0.3294          | 0.8894                        | 0.8807                     | 0.8849                 | 0.3397 | 33.2    |


### Framework versions

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