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---
license: apache-2.0
base_model: facebook/bart-base
tags:
- generated_from_trainer
model-index:
- name: pubmed-abs-ins-con-04
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. -->
# pubmed-abs-ins-con-04
This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co./facebook/bart-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0614
## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.1838 | 0.11 | 500 | 0.1188 |
| 0.1451 | 0.21 | 1000 | 0.1138 |
| 0.1363 | 0.32 | 1500 | 0.0935 |
| 0.2084 | 0.43 | 2000 | 0.0868 |
| 0.1054 | 0.54 | 2500 | 0.0866 |
| 0.1228 | 0.64 | 3000 | 0.0789 |
| 0.0911 | 0.75 | 3500 | 0.0771 |
| 0.1134 | 0.86 | 4000 | 0.0733 |
| 0.0853 | 0.96 | 4500 | 0.0727 |
| 0.0822 | 1.07 | 5000 | 0.0734 |
| 0.0699 | 1.18 | 5500 | 0.0716 |
| 0.0767 | 1.28 | 6000 | 0.0741 |
| 0.0675 | 1.39 | 6500 | 0.0713 |
| 0.0724 | 1.5 | 7000 | 0.0693 |
| 0.0643 | 1.61 | 7500 | 0.0674 |
| 0.0614 | 1.71 | 8000 | 0.0668 |
| 0.1225 | 1.82 | 8500 | 0.0633 |
| 0.0704 | 1.93 | 9000 | 0.0623 |
| 0.055 | 2.03 | 9500 | 0.0660 |
| 0.0567 | 2.14 | 10000 | 0.0633 |
| 0.052 | 2.25 | 10500 | 0.0658 |
| 0.0459 | 2.35 | 11000 | 0.0644 |
| 0.0572 | 2.46 | 11500 | 0.0628 |
| 0.0604 | 2.57 | 12000 | 0.0615 |
| 0.0516 | 2.68 | 12500 | 0.0611 |
| 0.0424 | 2.78 | 13000 | 0.0616 |
| 0.0385 | 2.89 | 13500 | 0.0615 |
| 0.0448 | 3.0 | 14000 | 0.0614 |
### Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0
- Datasets 2.14.7
- Tokenizers 0.14.1
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