transformers pytorch bart text2text-generation generated_from_trainer dataset:clupubhealth base_model:facebook/bart-large-cnn base_model:finetune:facebook/bart-large-cnn license:mit model-index autotrain_compatible endpoints_compatible region:us
---
base_model: facebook/bart-large-cnn
datasets:
- clupubhealth
license: mit
metrics:
- rouge
tags:
- generated_from_trainer
model-index:
- name: bart-cnn-pubhealth-expanded-hi-grad
  results:
  - task:
      type: text2text-generation
      name: Sequence-to-sequence Language Modeling
    dataset:
      name: clupubhealth
      type: clupubhealth
      config: expanded
      split: test
      args: expanded
    metrics:
    - type: rouge
      value: 28.8807
      name: Rouge1
---

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# bart-cnn-pubhealth-expanded-hi-grad

This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on the clupubhealth dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1939
- Rouge1: 28.8807
- Rouge2: 8.9567
- Rougel: 19.5591
- Rougelsum: 20.6726
- Gen Len: 66.99

## 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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 950
- total_train_batch_size: 15200
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
| 3.4166        | 0.49  | 2    | 2.4019          | 22.0991 | 4.6789 | 15.1628 | 17.4382   | 75.065  |
| 3.2194        | 0.98  | 4    | 2.3372          | 25.0981 | 6.6975 | 17.4606 | 19.2018   | 71.225  |
| 3.0969        | 1.47  | 6    | 2.2979          | 26.4747 | 7.1948 | 18.2262 | 19.6241   | 67.19   |
| 3.0313        | 1.96  | 8    | 2.3038          | 26.8637 | 7.5831 | 18.2923 | 19.6327   | 66.875  |
| 2.9753        | 2.44  | 10   | 2.2976          | 27.8942 | 8.3434 | 19.095  | 20.6248   | 67.975  |
| 2.9296        | 2.93  | 12   | 2.2602          | 28.1255 | 8.6477 | 19.0575 | 20.7787   | 68.515  |
| 2.8681        | 3.42  | 14   | 2.2341          | 28.0812 | 8.598  | 19.3391 | 20.7526   | 68.285  |
| 2.867         | 3.91  | 16   | 2.2246          | 28.3624 | 8.7921 | 19.5552 | 21.1147   | 68.225  |
| 2.8157        | 4.4   | 18   | 2.2178          | 28.8197 | 8.8423 | 19.3606 | 20.698    | 69.08   |
| 2.8007        | 4.89  | 20   | 2.2149          | 28.34   | 8.5084 | 18.8293 | 20.1169   | 68.255  |
| 2.7797        | 5.38  | 22   | 2.2123          | 28.2156 | 8.4891 | 19.3472 | 20.5036   | 67.525  |
| 2.7563        | 5.87  | 24   | 2.2083          | 27.8927 | 8.3783 | 19.1194 | 20.2498   | 68.365  |
| 2.736         | 6.36  | 26   | 2.2035          | 28.2588 | 8.2345 | 18.9418 | 20.2931   | 68.335  |
| 2.7208        | 6.85  | 28   | 2.2020          | 28.2471 | 8.599  | 19.3465 | 20.5104   | 68.44   |
| 2.713         | 7.33  | 30   | 2.2022          | 28.1863 | 8.5142 | 19.194  | 20.2467   | 68.3    |
| 2.7135        | 7.82  | 32   | 2.2013          | 28.462  | 8.6346 | 19.2465 | 20.4812   | 68.195  |
| 2.6987        | 8.31  | 34   | 2.1988          | 28.9168 | 8.8888 | 19.6491 | 20.7796   | 67.275  |
| 2.6978        | 8.8   | 36   | 2.1965          | 28.7303 | 8.9879 | 19.5924 | 20.6943   | 67.31   |
| 2.6769        | 9.29  | 38   | 2.1946          | 28.7956 | 8.9652 | 19.545  | 20.7352   | 67.33   |
| 2.6821        | 9.78  | 40   | 2.1939          | 28.8807 | 8.9567 | 19.5591 | 20.6726   | 66.99   |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2
