transformers safetensors bart text2text-generation generated_from_trainer base_model:facebook/bart-base license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: facebook/bart-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-base-arxiv-1024
  results: []
---

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# bart-base-arxiv-1024

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: 4.4204
- Rouge1: 42.7148
- Rouge2: 14.9393
- Rougel: 23.8135
- Rougelsum: 38.2094
- Gen Len: 152.94

## 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: 0.0008
- train_batch_size: 16
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: polynomial
- lr_scheduler_warmup_steps: 500
- num_epochs: 4
- mixed_precision_training: Native AMP
- label_smoothing_factor: 0.2

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 5.0132        | 0.16  | 500   | 4.9526          | 36.6006 | 11.6516 | 21.2812 | 32.3855   | 102.5   |
| 4.9026        | 0.32  | 1000  | 4.8487          | 37.0279 | 11.9575 | 21.6566 | 33.3527   | 98.72   |
| 4.8134        | 0.47  | 1500  | 4.8093          | 38.6789 | 12.0964 | 21.5679 | 34.4042   | 131.17  |
| 4.7615        | 0.63  | 2000  | 4.7357          | 38.9948 | 12.6214 | 21.5771 | 34.6947   | 120.84  |
| 4.7316        | 0.79  | 2500  | 4.6984          | 39.0043 | 13.692  | 22.4767 | 34.7406   | 114.67  |
| 4.6984        | 0.95  | 3000  | 4.6661          | 37.7638 | 13.0795 | 21.9015 | 34.1801   | 112.11  |
| 4.6423        | 1.1   | 3500  | 4.6413          | 40.2953 | 13.9014 | 22.6632 | 35.9141   | 127.43  |
| 4.6166        | 1.26  | 4000  | 4.6175          | 40.99   | 14.3428 | 23.4201 | 36.6002   | 133.73  |
| 4.5878        | 1.42  | 4500  | 4.6042          | 40.8889 | 14.0993 | 23.0454 | 36.9924   | 141.88  |
| 4.5874        | 1.58  | 5000  | 4.5846          | 39.9072 | 14.2083 | 22.8314 | 35.9495   | 123.82  |
| 4.5642        | 1.73  | 5500  | 4.5687          | 40.4716 | 14.1263 | 22.6271 | 36.2139   | 137.2   |
| 4.555         | 1.89  | 6000  | 4.5551          | 41.3314 | 14.232  | 22.8318 | 37.1038   | 148.78  |
| 4.4763        | 2.05  | 6500  | 4.5433          | 41.7555 | 14.6625 | 23.7076 | 37.705    | 142.12  |
| 4.4687        | 2.21  | 7000  | 4.5232          | 41.226  | 14.6976 | 23.0482 | 36.7016   | 133.7   |
| 4.4737        | 2.37  | 7500  | 4.5128          | 40.0649 | 13.9868 | 23.1803 | 35.9016   | 122.17  |
| 4.4634        | 2.52  | 8000  | 4.4999          | 42.5774 | 15.4706 | 23.4321 | 38.212    | 137.87  |
| 4.4443        | 2.68  | 8500  | 4.4829          | 41.7603 | 15.1096 | 23.5735 | 37.5121   | 147.78  |
| 4.4409        | 2.84  | 9000  | 4.4757          | 41.9056 | 14.7477 | 23.1478 | 37.6321   | 142.64  |
| 4.4271        | 3.0   | 9500  | 4.4642          | 41.7456 | 15.1452 | 23.4016 | 37.6441   | 138.98  |
| 4.3629        | 3.15  | 10000 | 4.4569          | 41.5637 | 15.0198 | 23.0226 | 37.22     | 148.2   |
| 4.3489        | 3.31  | 10500 | 4.4502          | 42.0897 | 14.7576 | 23.1048 | 37.6046   | 142.48  |
| 4.3377        | 3.47  | 11000 | 4.4403          | 43.3032 | 15.4076 | 23.665  | 39.0579   | 156.0   |
| 4.339         | 3.63  | 11500 | 4.4329          | 42.6232 | 15.0481 | 23.6074 | 37.637    | 151.36  |
| 4.3423        | 3.78  | 12000 | 4.4272          | 42.565  | 14.9409 | 23.2332 | 38.1214   | 154.21  |
| 4.3269        | 3.94  | 12500 | 4.4204          | 42.7148 | 14.9393 | 23.8135 | 38.2094   | 152.94  |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.15.2
