---
license: mit
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-large-cnn-finetuned-roundup-8
  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-roundup-8

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: 1.4519
- Rouge1: 49.5671
- Rouge2: 27.0118
- Rougel: 30.8538
- Rougelsum: 45.5503
- Gen Len: 141.75

## 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| No log        | 1.0   | 132  | 1.3159          | 48.5275 | 28.0817 | 30.6646 | 45.5024   | 142.0   |
| No log        | 2.0   | 264  | 1.2377          | 47.0791 | 27.4386 | 28.9458 | 44.1536   | 142.0   |
| No log        | 3.0   | 396  | 1.2474          | 49.3567 | 29.5904 | 30.8029 | 46.6083   | 142.0   |
| 0.9623        | 4.0   | 528  | 1.2914          | 47.8795 | 27.0611 | 29.8538 | 44.4494   | 142.0   |
| 0.9623        | 5.0   | 660  | 1.2982          | 49.9921 | 28.4839 | 31.5688 | 46.9734   | 142.0   |
| 0.9623        | 6.0   | 792  | 1.3521          | 46.7269 | 25.8672 | 29.7325 | 43.8279   | 142.0   |
| 0.9623        | 7.0   | 924  | 1.4102          | 47.4995 | 26.0066 | 29.4342 | 44.1102   | 141.8   |
| 0.3734        | 8.0   | 1056 | 1.4519          | 49.5671 | 27.0118 | 30.8538 | 45.5503   | 141.75  |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.11.0+cu113
- Datasets 2.1.0
- Tokenizers 0.12.1