transformers tensorboard safetensors bart text2text-generation generated_from_trainer base_model:facebook/bart-large-cnn license:mit autotrain_compatible endpoints_compatible region:us
---
license: mit
base_model: facebook/bart-large-cnn
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-large-cnn-finetuned-scope-summarization
  results: []
---

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# bart-large-cnn-finetuned-scope-summarization

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: 0.1309
- Rouge1: 52.6236
- Rouge2: 39.8632
- Rougel: 43.4607
- Rougelsum: 43.3561

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 0.5104        | 1.0   | 34   | 0.2207          | 41.732  | 26.7717 | 31.2807 | 31.3611   |
| 0.2181        | 2.0   | 68   | 0.2001          | 44.5268 | 30.0523 | 34.7912 | 35.0095   |
| 0.1824        | 3.0   | 102  | 0.1995          | 45.4038 | 32.6808 | 36.3856 | 36.4004   |
| 0.1851        | 4.0   | 136  | 0.1728          | 48.85   | 35.9202 | 39.2826 | 39.1813   |
| 0.1692        | 5.0   | 170  | 0.1663          | 47.1374 | 34.5505 | 37.8192 | 37.8176   |
| 0.164         | 6.0   | 204  | 0.1594          | 50.3895 | 37.8751 | 40.4181 | 40.3778   |
| 0.1534        | 7.0   | 238  | 0.1526          | 50.7178 | 38.8207 | 41.5719 | 41.6111   |
| 0.1421        | 8.0   | 272  | 0.1424          | 51.3382 | 38.6796 | 40.4545 | 40.3891   |
| 0.1423        | 9.0   | 306  | 0.1354          | 53.8161 | 41.0736 | 45.1571 | 45.0427   |
| 0.1336        | 10.0  | 340  | 0.1309          | 52.6236 | 39.8632 | 43.4607 | 43.3561   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
