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---
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-48
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-48
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: 2.1260
- Rouge1: 0.4187
- Rouge2: 0.2233
- Rougel: 0.3553
- Rougelsum: 0.3545
- Gen Len: 18.201
## 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: 48
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 2.6968 | 1.0 | 1250 | 2.1990 | 0.4139 | 0.2206 | 0.353 | 0.3525 | 17.88 |
| 2.6029 | 2.0 | 2500 | 2.1650 | 0.415 | 0.2192 | 0.351 | 0.3503 | 18.142 |
| 2.5682 | 3.0 | 3750 | 2.1438 | 0.4162 | 0.2188 | 0.35 | 0.3495 | 18.151 |
| 2.5281 | 4.0 | 5000 | 2.1297 | 0.4189 | 0.223 | 0.3559 | 0.3553 | 18.287 |
| 2.5228 | 5.0 | 6250 | 2.1269 | 0.4175 | 0.2228 | 0.3551 | 0.3545 | 18.157 |
| 2.542 | 6.0 | 7500 | 2.1260 | 0.4187 | 0.2233 | 0.3553 | 0.3545 | 18.201 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |