---
base_model: facebook/bart-base
library_name: peft
license: apache-2.0
metrics:
- rouge
tags:
- generated_from_trainer
model-index:
- name: bart-base-summarization-medical-50
  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-base-summarization-medical-50

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: 2.1337
- Rouge1: 0.4177
- Rouge2: 0.2219
- Rougel: 0.3529
- Rougelsum: 0.3526
- Gen Len: 18.32

## 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: 3e-05
- train_batch_size: 4
- eval_batch_size: 1
- seed: 50
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 2.705         | 1.0   | 1250 | 2.1960          | 0.4122 | 0.2191 | 0.3515 | 0.3514    | 17.971  |
| 2.5847        | 2.0   | 2500 | 2.1640          | 0.414  | 0.2185 | 0.3495 | 0.3493    | 18.179  |
| 2.564         | 3.0   | 3750 | 2.1490          | 0.4165 | 0.2208 | 0.3519 | 0.3516    | 18.135  |
| 2.559         | 4.0   | 5000 | 2.1389          | 0.4161 | 0.2215 | 0.352  | 0.3518    | 18.26   |
| 2.5562        | 5.0   | 6250 | 2.1367          | 0.4165 | 0.2211 | 0.3517 | 0.3514    | 18.297  |
| 2.5298        | 6.0   | 7500 | 2.1337          | 0.4177 | 0.2219 | 0.3529 | 0.3526    | 18.32   |


### Framework versions

- PEFT 0.12.0
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1