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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-base-finetuned-xsum
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-base-finetuned-xsum
This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co./facebook/bart-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7802
- Rouge1: 10.2407
- Rouge2: 5.6898
- Rougel: 8.8732
- Rougelsum: 9.8768
- Gen Len: 20.0
## 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: 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 | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:------:|:---------:|:-------:|
| 3.1154 | 1.0 | 501 | 2.1511 | 10.4364 | 5.0268 | 8.8521 | 9.977 | 19.982 |
| 2.1503 | 2.0 | 1002 | 1.9367 | 10.2402 | 5.6448 | 8.95 | 9.9444 | 20.0 |
| 1.9303 | 3.0 | 1503 | 1.8703 | 10.4716 | 5.8584 | 9.091 | 10.1726 | 20.0 |
| 1.8227 | 4.0 | 2004 | 1.8365 | 10.3486 | 5.6575 | 8.9376 | 10.0274 | 20.0 |
| 1.7561 | 5.0 | 2505 | 1.8137 | 10.3933 | 5.7567 | 8.9715 | 10.0342 | 20.0 |
| 1.6962 | 6.0 | 3006 | 1.7963 | 10.3287 | 5.7717 | 8.9701 | 10.0094 | 20.0 |
| 1.6573 | 7.0 | 3507 | 1.7906 | 10.2815 | 5.6978 | 8.9025 | 9.9513 | 20.0 |
| 1.6357 | 8.0 | 4008 | 1.7808 | 10.3892 | 5.78 | 9.0166 | 10.0314 | 20.0 |
| 1.6269 | 9.0 | 4509 | 1.7808 | 10.2931 | 5.7193 | 8.9356 | 9.9356 | 20.0 |
| 1.6031 | 10.0 | 5010 | 1.7802 | 10.2407 | 5.6898 | 8.8732 | 9.8768 | 20.0 |
### Framework versions
- Transformers 4.30.2
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3
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