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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_on_cnn-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_on_cnn-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: 3.3893
- Rouge1: 0.2525
- Rouge2: 0.0944
- Rougel: 0.2
- Rougelsum: 0.2242
- Gen Len: 18.451
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 2.6901 | 1.0 | 1250 | 3.3869 | 0.2516 | 0.0884 | 0.1964 | 0.2218 | 19.066 |
| 2.6035 | 2.0 | 2500 | 3.3751 | 0.2516 | 0.0926 | 0.1975 | 0.2231 | 18.716 |
| 2.564 | 3.0 | 3750 | 3.3818 | 0.2503 | 0.0926 | 0.1974 | 0.2221 | 18.501 |
| 2.5265 | 4.0 | 5000 | 3.3882 | 0.2505 | 0.0927 | 0.1979 | 0.2219 | 18.482 |
| 2.5207 | 5.0 | 6250 | 3.3881 | 0.2532 | 0.0946 | 0.2005 | 0.2247 | 18.394 |
| 2.5356 | 6.0 | 7500 | 3.3893 | 0.2525 | 0.0944 | 0.2 | 0.2242 | 18.451 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |