---
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-49
  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-49

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: 2.1283
- Rouge1: 0.4194
- Rouge2: 0.2246
- Rougel: 0.3563
- Rougelsum: 0.356
- Gen Len: 18.24

## 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: 49
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 2.7018        | 1.0   | 1250 | 2.1985          | 0.4123 | 0.2198 | 0.352  | 0.3522    | 17.961  |
| 2.6001        | 2.0   | 2500 | 2.1649          | 0.4125 | 0.2205 | 0.3526 | 0.3526    | 17.963  |
| 2.577         | 3.0   | 3750 | 2.1418          | 0.4189 | 0.222  | 0.3547 | 0.3548    | 18.185  |
| 2.5295        | 4.0   | 5000 | 2.1347          | 0.4213 | 0.2256 | 0.3564 | 0.3559    | 18.174  |
| 2.5513        | 5.0   | 6250 | 2.1299          | 0.4174 | 0.2224 | 0.3545 | 0.3542    | 18.118  |
| 2.5347        | 6.0   | 7500 | 2.1283          | 0.4194 | 0.2246 | 0.3563 | 0.356     | 18.24   |


### Framework versions

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