---
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-44
  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-44

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: 2.1287
- Rouge1: 0.4223
- Rouge2: 0.2251
- Rougel: 0.3572
- Rougelsum: 0.357
- Gen Len: 18.196

## 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: 44
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 2.7031        | 1.0   | 1250 | 2.1999          | 0.413  | 0.2201 | 0.3533 | 0.3528    | 17.704  |
| 2.6144        | 2.0   | 2500 | 2.1644          | 0.4143 | 0.2198 | 0.3521 | 0.3518    | 17.965  |
| 2.5745        | 3.0   | 3750 | 2.1561          | 0.4142 | 0.2169 | 0.3486 | 0.3483    | 18.171  |
| 2.5622        | 4.0   | 5000 | 2.1389          | 0.419  | 0.2222 | 0.3523 | 0.3524    | 18.221  |
| 2.5308        | 5.0   | 6250 | 2.1308          | 0.422  | 0.2255 | 0.3569 | 0.3569    | 18.183  |
| 2.5394        | 6.0   | 7500 | 2.1287          | 0.4223 | 0.2251 | 0.3572 | 0.357     | 18.196  |


### Framework versions

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