---
license: mit
base_model: facebook/bart-large-cnn
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-large-cnn-finetuned-scope1-summarization
  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-scope1-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: 0.0612
- Rouge1: 55.9874
- Rouge2: 41.0458
- Rougel: 47.6072
- Rougelsum: 47.5635

## 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: 16
- eval_batch_size: 16
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| No log        | 1.0   | 17   | 0.1238          | 46.7806 | 30.4394 | 36.8259 | 36.8757   |
| 0.4762        | 2.0   | 34   | 0.1058          | 49.4907 | 32.4075 | 39.352  | 39.161    |
| 0.4762        | 3.0   | 51   | 0.0899          | 54.1557 | 35.6198 | 41.6488 | 41.4013   |
| 0.1104        | 4.0   | 68   | 0.0867          | 53.237  | 36.766  | 42.8508 | 42.7151   |
| 0.1104        | 5.0   | 85   | 0.0773          | 57.4084 | 39.3354 | 45.068  | 44.9505   |
| 0.0914        | 6.0   | 102  | 0.0736          | 56.9111 | 41.3118 | 48.1607 | 47.9965   |
| 0.0914        | 7.0   | 119  | 0.0699          | 58.6135 | 42.3985 | 48.7923 | 48.4873   |
| 0.0785        | 8.0   | 136  | 0.0673          | 59.5593 | 43.9205 | 51.7275 | 51.5617   |
| 0.0785        | 9.0   | 153  | 0.0618          | 62.0583 | 47.3928 | 53.3198 | 53.1472   |
| 0.0702        | 10.0  | 170  | 0.0612          | 55.9874 | 41.0458 | 47.6072 | 47.5635   |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1