---
license: mit
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-large-cnn-finetuned-roundup-4-16
  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-4-16

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: 0.8760
- Rouge1: 56.3338
- Rouge2: 42.4032
- Rougel: 45.9455
- Rougelsum: 54.6488
- Gen Len: 142.0

## 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: 16
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len  |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
| No log        | 1.0   | 398  | 0.9325          | 52.7796 | 33.0802 | 34.8217 | 50.2211   | 142.0    |
| 1.1317        | 2.0   | 796  | 0.8313          | 53.6274 | 35.3235 | 37.7077 | 51.0888   | 141.2963 |
| 0.6757        | 3.0   | 1194 | 0.7893          | 54.1449 | 34.7532 | 36.3211 | 51.781    | 142.0    |
| 0.4511        | 4.0   | 1592 | 0.7647          | 52.2694 | 34.2286 | 36.5736 | 49.7078   | 142.0    |
| 0.4511        | 5.0   | 1990 | 0.7596          | 55.1986 | 37.5865 | 41.406  | 53.1897   | 141.8333 |
| 0.3037        | 6.0   | 2388 | 0.7688          | 53.9367 | 36.8729 | 39.9456 | 51.5108   | 142.0    |
| 0.209         | 7.0   | 2786 | 0.7590          | 54.6867 | 37.6415 | 41.2602 | 52.746    | 142.0    |
| 0.1452        | 8.0   | 3184 | 0.7744          | 53.5374 | 36.3666 | 40.0432 | 51.3461   | 142.0    |
| 0.11          | 9.0   | 3582 | 0.8042          | 56.6623 | 40.4702 | 44.0028 | 54.5138   | 142.0    |
| 0.11          | 10.0  | 3980 | 0.8105          | 55.6002 | 40.5663 | 43.8119 | 53.9117   | 142.0    |
| 0.0833        | 11.0  | 4378 | 0.8230          | 56.2517 | 40.8567 | 44.0009 | 54.3271   | 142.0    |
| 0.0634        | 12.0  | 4776 | 0.8329          | 55.9228 | 40.6443 | 43.6161 | 54.0975   | 142.0    |
| 0.0474        | 13.0  | 5174 | 0.8570          | 55.4923 | 40.3683 | 43.4675 | 53.404    | 142.0    |
| 0.0349        | 14.0  | 5572 | 0.8658          | 56.4454 | 41.8069 | 44.2922 | 54.464    | 142.0    |
| 0.0349        | 15.0  | 5970 | 0.8754          | 56.3837 | 42.2025 | 45.7817 | 54.4912   | 142.0    |
| 0.0304        | 16.0  | 6368 | 0.8760          | 56.3338 | 42.4032 | 45.9455 | 54.6488   | 142.0    |


### Framework versions

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