---
language:
- en
tags:
- summarization
datasets:
- scientific_papers
metrics:
- rouge
model-index:
- name: ccdv/lsg-bart-base-4096-pubmed
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

**This model relies on a custom modeling file, you need to add trust_remote_code=True**\
**See [\#13467](https://github.com/huggingface/transformers/pull/13467)**

# ccdv/lsg-bart-base-4096-pubmed

This model is a fine-tuned version of [ccdv/lsg-bart-base-4096](https://huggingface.co/ccdv/lsg-bart-base-4096) on the scientific_papers pubmed dataset. \
It achieves the following results on the test set:

| Length | Sparse Type | Block Size | Sparsity | Connexions | R1    | R2    | RL    | RLsum |
|:------ |:----------- |:---------- |:-------- | :--------- |:----- |:----- |:----- |:----- |
| 4096   | Local       | 256        | 0        | 768        | 47.33 | 21.67 | 28.53 | 43.67 |
| 4096   | Local       | 128        | 0        | 384        | 46.84 | 21.24 | 28.22 | 43.15 |
| 4096   | Pooling     | 128        | 4        | 644        | 47.07 | 21.41 | 28.40 | 43.36 |
| 4096   | Stride      | 128        | 4        | 644        | 47.02 | 21.46 | 28.33 | 43.35 |
| 4096   | Norm        | 128        | 4        | 644        | 47.01 | 21.32 | 28.26 | 43.33 |
| 4096   | LSH         | 128        | 4        | 644        | 46.92 | 21.27 | 28.26 | 43.26 |



## Model description
The model relies on Local-Sparse-Global attention to handle long sequences:
![attn](attn.png)

The model has about ~145 millions parameters (6 encoder layers - 6 decoder layers). \
The model is warm started from BART-base, converted to handle long sequences (encoder only) and fine tuned. \

## 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: 8e-05
- train_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7.0

### Generate hyperparameters

The following hyperparameters were used during generation:
- dataset_name: scientific_papers
- dataset_config_name: pubmed
- eval_batch_size: 8
- early_stopping: True
- ignore_pad_token_for_loss: True
- length_penalty: 2.0
- max_length: 512
- min_length: 128
- num_beams: 5
- num_samples: None
- no_repeat_ngram_size: None
- seed: 123

### Framework versions

- Transformers 4.18.0
- Pytorch 1.10.1+cu102
- Datasets 2.1.0
- Tokenizers 0.11.6