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---
license: apache-2.0
base_model: facebook/bart-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-base-finetuned-explanation
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-explanation
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: 0.2148
- Rouge1: 0.1029
- Rouge2: 0.0092
- Rougel: 0.1032
- Rougelsum: 0.1037
## 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: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 2.8399 | 1.0 | 119 | 0.2340 | 0.0924 | 0.0061 | 0.0882 | 0.0871 |
| 0.2248 | 2.0 | 238 | 0.2141 | 0.0964 | 0.0094 | 0.0891 | 0.0902 |
| 0.179 | 3.0 | 357 | 0.2148 | 0.1029 | 0.0092 | 0.1032 | 0.1037 |
### Framework versions
- Transformers 4.41.2
- Pytorch 1.11.0
- Datasets 2.19.2
- Tokenizers 0.19.1
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