---
base_model: ccdv/lsg-bart-base-16384-mediasum
tags:
- generated_from_trainer
datasets:
- pubmed-summarization
model-index:
- name: bart-fine-tuned-on-summarization
  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. -->

# bart-fine-tuned-on-summarization

This model is a fine-tuned version of [ccdv/lsg-bart-base-16384-mediasum](https://huggingface.co/ccdv/lsg-bart-base-16384-mediasum) on the pubmed-summarization dataset.
It achieves the following results on the evaluation set:
- Loss: 2.7293

## 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: 5e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 3.4477        | 0.2   | 100  | 3.1109          |
| 3.0893        | 0.4   | 200  | 2.8719          |
| 2.8441        | 0.6   | 300  | 2.7832          |
| 2.9203        | 0.8   | 400  | 2.7402          |
| 2.9796        | 1.0   | 500  | 2.7293          |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2