transformers pytorch tensorboard bart text2text-generation summarization generated_from_trainer dataset:arxiv_summarization_dataset dataset:ccdv/arxiv-summarization license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- arxiv_summarization_dataset
- ccdv/arxiv-summarization
license: apache-2.0
metrics:
- rouge
tags:
- summarization
- generated_from_trainer
model-index:
- name: bart-base-arxiv-sum-session-1
  results:
  - task:
      type: text2text-generation
      name: Sequence-to-sequence Language Modeling
    dataset:
      name: arxiv_summarization_dataset
      type: arxiv_summarization_dataset
      config: section
      split: validation
      args: section
    metrics:
    - type: rouge
      value: 12.7479
      name: Rouge1
---

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# bart-base-arxiv-sum-session-1

This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the arxiv_summarization_dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 2.8862
- Rouge1: 12.7479
- Rouge2: 4.8295
- Rougel: 10.2761
- Rougelsum: 11.7334

## Model description

Model obtained from fine-tuning facebook/bart-base on 25,000 training samples from the ccdv/arxiv-summarization dataset.

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| No log        | 1.0   | 195  | 2.9794          | 12.5852 | 4.6927 | 10.1374 | 11.6014   |
| No log        | 2.0   | 390  | 2.9077          | 12.5854 | 4.7568 | 10.166  | 11.5699   |
| No log        | 3.0   | 585  | 2.8862          | 12.7479 | 4.8295 | 10.2761 | 11.7334   |


### Framework versions

- Transformers 4.27.4
- Pytorch 1.13.0
- Datasets 2.1.0
- Tokenizers 0.13.2