---
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-45
  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-45

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: 2.1275
- Rouge1: 0.4196
- Rouge2: 0.2244
- Rougel: 0.3562
- Rougelsum: 0.3564
- Gen Len: 18.338

## 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: 45
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 2.6973        | 1.0   | 1250 | 2.1978          | 0.4152 | 0.2215 | 0.3551 | 0.3555    | 17.896  |
| 2.6015        | 2.0   | 2500 | 2.1713          | 0.4141 | 0.2205 | 0.3511 | 0.3508    | 18.338  |
| 2.5775        | 3.0   | 3750 | 2.1466          | 0.4165 | 0.2208 | 0.3514 | 0.3515    | 18.41   |
| 2.5536        | 4.0   | 5000 | 2.1345          | 0.4214 | 0.2241 | 0.358  | 0.3579    | 18.38   |
| 2.5322        | 5.0   | 6250 | 2.1279          | 0.4226 | 0.2257 | 0.3587 | 0.3587    | 18.447  |
| 2.5289        | 6.0   | 7500 | 2.1275          | 0.4196 | 0.2244 | 0.3562 | 0.3564    | 18.338  |


### Framework versions

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