pytorch tensorboard bart text2text-generation transformers generated_from_trainer license:mit model-index autotrain_compatible
---
license: mit
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-large-cnn-finetuned-pubmed-finetuned-roundup-e16
  results: []
---

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# bart-large-cnn-finetuned-pubmed-finetuned-roundup-e16

This model is a fine-tuned version of [theojolliffe/bart-large-cnn-finetuned-pubmed](https://huggingface.co/theojolliffe/bart-large-cnn-finetuned-pubmed) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6815
- Rouge1: 48.7608
- Rouge2: 29.554
- Rougel: 30.5554
- Rougelsum: 46.4001
- Gen Len: 142.0

## 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: 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: 16
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| No log        | 1.0   | 25   | 1.4287          | 46.5701 | 28.6267 | 34.7827 | 45.0622   | 142.0   |
| No log        | 2.0   | 50   | 1.4419          | 46.6171 | 27.4276 | 31.0085 | 43.1797   | 142.0   |
| No log        | 3.0   | 75   | 1.5418          | 50.1144 | 29.3433 | 32.0144 | 46.9217   | 142.0   |
| No log        | 4.0   | 100  | 1.7125          | 49.1395 | 28.611  | 30.9759 | 46.8346   | 142.0   |
| No log        | 5.0   | 125  | 1.8978          | 43.9629 | 24.1224 | 26.0032 | 41.2272   | 142.0   |
| No log        | 6.0   | 150  | 2.0990          | 49.0579 | 29.5182 | 31.5829 | 46.0207   | 142.0   |
| No log        | 7.0   | 175  | 2.2380          | 48.8754 | 27.7691 | 28.8597 | 45.3281   | 142.0   |
| No log        | 8.0   | 200  | 2.2922          | 48.311  | 29.2517 | 33.8241 | 46.6099   | 142.0   |
| No log        | 9.0   | 225  | 2.3820          | 45.4663 | 23.9904 | 27.5497 | 41.9446   | 142.0   |
| No log        | 10.0  | 250  | 2.4856          | 48.2224 | 27.7455 | 28.159  | 45.4726   | 142.0   |
| No log        | 11.0  | 275  | 2.4731          | 46.1799 | 22.1941 | 26.8254 | 43.9986   | 142.0   |
| No log        | 12.0  | 300  | 2.5278          | 47.8623 | 27.6514 | 26.6377 | 42.9255   | 142.0   |
| No log        | 13.0  | 325  | 2.6229          | 45.573  | 25.4966 | 27.7158 | 42.2306   | 142.0   |
| No log        | 14.0  | 350  | 2.6032          | 48.1972 | 27.0387 | 28.336  | 45.0293   | 142.0   |
| No log        | 15.0  | 375  | 2.6600          | 47.7301 | 27.3567 | 29.3389 | 44.3516   | 142.0   |
| No log        | 16.0  | 400  | 2.6815          | 48.7608 | 29.554  | 30.5554 | 46.4001   | 142.0   |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.11.0+cu113
- Datasets 2.1.0
- Tokenizers 0.12.1
