pytorch tensorboard bart text2text-generation transformers generated_from_trainer license:apache-2.0 model-index autotrain_compatible
---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-paraphrase-finetuned-xsum-v3
  results: []
---

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# bart-paraphrase-finetuned-xsum-v3

This model is a fine-tuned version of [eugenesiow/bart-paraphrase](https://huggingface.co/eugenesiow/bart-paraphrase) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1881
- Rouge1: 99.9251
- Rouge2: 99.9188
- Rougel: 99.9251
- Rougelsum: 99.9251
- Gen Len: 10.17

## 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: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| No log        | 1.0   | 100  | 0.2702          | 99.9251 | 99.9188 | 99.9251 | 99.9251   | 10.38   |
| No log        | 2.0   | 200  | 0.2773          | 99.9251 | 99.9188 | 99.9251 | 99.9251   | 11.45   |
| No log        | 3.0   | 300  | 0.2178          | 99.8148 | 99.7051 | 99.8208 | 99.8148   | 11.19   |
| No log        | 4.0   | 400  | 0.3649          | 99.9251 | 99.9188 | 99.9251 | 99.9251   | 12.32   |
| 0.1561        | 5.0   | 500  | 0.2532          | 99.8957 | 99.8875 | 99.8957 | 99.8918   | 10.375  |
| 0.1561        | 6.0   | 600  | 0.2050          | 99.9251 | 99.9188 | 99.9251 | 99.9251   | 11.15   |
| 0.1561        | 7.0   | 700  | 0.2364          | 99.8957 | 99.8875 | 99.8957 | 99.8918   | 10.18   |
| 0.1561        | 8.0   | 800  | 0.2006          | 99.9251 | 99.9188 | 99.9251 | 99.9251   | 10.17   |
| 0.1561        | 9.0   | 900  | 0.1628          | 99.9251 | 99.9188 | 99.9251 | 99.9251   | 10.23   |
| 0.1538        | 10.0  | 1000 | 0.1881          | 99.9251 | 99.9188 | 99.9251 | 99.9251   | 10.17   |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
