---
license: mit
base_model: facebook/bart-large-cnn
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-large-cnn-with-generate-finetune-indosum
  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-with-generate-finetune-indosum

This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co./facebook/bart-large-cnn) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0686
- Rouge1: 0.8873
- Rouge2: 0.8491
- Rougel: 0.8815
- Rougelsum: 0.8815
- Gen Len: 128.9129

## 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: 2e-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 | Gen Len  |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:--------:|
| 0.2591        | 1.0   | 4460  | 0.2573          | 0.7218 | 0.6324 | 0.6969 | 0.6967    | 129.0612 |
| 0.1657        | 2.0   | 8920  | 0.1600          | 0.7613 | 0.6815 | 0.7401 | 0.7401    | 128.9508 |
| 0.0945        | 3.0   | 13380 | 0.1157          | 0.8001 | 0.7311 | 0.7837 | 0.7835    | 128.9105 |
| 0.0508        | 4.0   | 17840 | 0.0976          | 0.8277 | 0.7704 | 0.8152 | 0.8152    | 129.0289 |
| 0.0296        | 5.0   | 22300 | 0.0853          | 0.857  | 0.8087 | 0.8473 | 0.8471    | 128.9257 |
| 0.0176        | 6.0   | 26760 | 0.0793          | 0.8702 | 0.8279 | 0.8632 | 0.8633    | 128.9113 |
| 0.0112        | 7.0   | 31220 | 0.0605          | 0.8789 | 0.8377 | 0.872  | 0.8721    | 128.8637 |
| 0.0074        | 8.0   | 35680 | 0.0597          | 0.88   | 0.84   | 0.8731 | 0.8732    | 128.9305 |
| 0.005         | 9.0   | 40140 | 0.0658          | 0.8822 | 0.8433 | 0.8761 | 0.8761    | 128.949  |
| 0.0036        | 10.0  | 44600 | 0.0686          | 0.8873 | 0.8491 | 0.8815 | 0.8815    | 128.9129 |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.0
- Datasets 2.12.0
- Tokenizers 0.13.2