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license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: BART_reddit_other
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_reddit_other
This model is a fine-tuned version of [sshleifer/distilbart-xsum-6-6](https://huggingface.co/sshleifer/distilbart-xsum-6-6) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.5792
- Rouge1: 18.5705
- Rouge2: 5.0107
- Rougel: 15.2581
- Rougelsum: 16.082
- Gen Len: 19.402
## 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: 3
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
| 3.7887 | 1.0 | 1875 | 3.6044 | 18.4668 | 5.182 | 15.359 | 16.169 | 19.341 |
| 3.3816 | 2.0 | 3750 | 3.5628 | 18.0998 | 4.8937 | 15.0179 | 15.7615 | 17.789 |
| 3.134 | 3.0 | 5625 | 3.5792 | 18.5705 | 5.0107 | 15.2581 | 16.082 | 19.402 |
### Framework versions
- Transformers 4.20.1
- Pytorch 1.12.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
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