---
license: mit
base_model: facebook/bart-large-cnn
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-large-cnn-finetuned-scope-summarization-train-test-split
  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-cnn-finetuned-scope-summarization-train-test-split

This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co./facebook/bart-large-cnn) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1824
- Rouge1: 50.8184
- Rouge2: 30.1612
- Rougel: 36.9904
- Rougelsum: 49.4235

## 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: 5.6e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| No log        | 1.0   | 34   | 0.7061          | 44.9133 | 26.0507 | 34.7329 | 43.2231   |
| 0.8927        | 2.0   | 68   | 0.7190          | 46.3702 | 26.952  | 36.2244 | 44.7608   |
| 0.617         | 3.0   | 102  | 0.6815          | 50.5658 | 28.4213 | 36.4503 | 49.3129   |
| 0.617         | 4.0   | 136  | 0.7083          | 50.7172 | 28.1621 | 37.0023 | 49.3293   |
| 0.5169        | 5.0   | 170  | 0.6819          | 50.0364 | 27.5729 | 35.9607 | 48.0331   |
| 0.4614        | 6.0   | 204  | 0.7171          | 51.0974 | 29.0043 | 36.4498 | 49.6124   |
| 0.3995        | 7.0   | 238  | 0.7577          | 50.8879 | 29.3509 | 35.9144 | 49.4029   |
| 0.3995        | 8.0   | 272  | 0.8192          | 50.332  | 28.9931 | 36.458  | 48.8301   |
| 0.3185        | 9.0   | 306  | 0.8635          | 49.4501 | 27.6673 | 35.7586 | 47.891    |
| 0.2627        | 10.0  | 340  | 0.9229          | 51.0907 | 30.1515 | 36.5669 | 49.6126   |
| 0.2627        | 11.0  | 374  | 0.9910          | 49.6877 | 29.4712 | 36.5784 | 48.6087   |
| 0.1952        | 12.0  | 408  | 1.0266          | 51.3167 | 30.619  | 36.5097 | 49.7864   |
| 0.1234        | 13.0  | 442  | 1.0313          | 49.6518 | 28.2854 | 35.9773 | 48.4327   |
| 0.0859        | 14.0  | 476  | 1.0791          | 50.3139 | 29.9343 | 35.8756 | 49.0233   |
| 0.0859        | 15.0  | 510  | 1.1431          | 50.4173 | 29.047  | 36.4338 | 48.8672   |
| 0.0591        | 16.0  | 544  | 1.1455          | 51.733  | 30.786  | 37.4082 | 50.4284   |
| 0.0448        | 17.0  | 578  | 1.1353          | 49.5046 | 29.3628 | 36.2758 | 48.324    |
| 0.0341        | 18.0  | 612  | 1.1619          | 51.7577 | 31.1043 | 37.9571 | 50.6969   |
| 0.0341        | 19.0  | 646  | 1.1748          | 51.4652 | 30.6309 | 36.7434 | 49.9184   |
| 0.0255        | 20.0  | 680  | 1.1824          | 50.8184 | 30.1612 | 36.9904 | 49.4235   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2