---
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-46
  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-46

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: 2.1274
- Rouge1: 0.4211
- Rouge2: 0.2237
- Rougel: 0.3559
- Rougelsum: 0.356
- Gen Len: 18.296

## 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: 46
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 2.7041        | 1.0   | 1250 | 2.2079          | 0.4109 | 0.2179 | 0.35   | 0.3501    | 18.052  |
| 2.6134        | 2.0   | 2500 | 2.1641          | 0.4151 | 0.2203 | 0.3517 | 0.3518    | 18.103  |
| 2.5664        | 3.0   | 3750 | 2.1450          | 0.4163 | 0.22   | 0.353  | 0.3529    | 18.051  |
| 2.5501        | 4.0   | 5000 | 2.1328          | 0.4191 | 0.2217 | 0.353  | 0.3528    | 18.228  |
| 2.535         | 5.0   | 6250 | 2.1268          | 0.4221 | 0.2253 | 0.3569 | 0.3568    | 18.235  |
| 2.5102        | 6.0   | 7500 | 2.1274          | 0.4211 | 0.2237 | 0.3559 | 0.356     | 18.296  |


### Framework versions

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