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---
license: mit
base_model: facebook/bart-large-xsum
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-large-xsum-dc
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-xsum-dc
This model is a fine-tuned version of [facebook/bart-large-xsum](https://huggingface.co./facebook/bart-large-xsum) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6335
- Rouge1: 32.0323
- Rouge2: 14.1008
- Rougel: 24.5596
- Rougelsum: 25.6498
## 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: 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: 4
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 1.9052 | 1.0 | 2676 | 1.7569 | 30.4785 | 12.762 | 23.1862 | 23.9824 |
| 1.4258 | 2.0 | 5352 | 1.5930 | 31.7087 | 13.5933 | 23.9115 | 24.7093 |
| 1.1141 | 3.0 | 8028 | 1.5729 | 32.3123 | 14.3572 | 24.8666 | 25.856 |
| 0.8621 | 4.0 | 10704 | 1.6335 | 32.0323 | 14.1008 | 24.5596 | 25.6498 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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