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---
license: apache-2.0
base_model: facebook/bart-base
tags:
- generated_from_trainer
model-index:
- name: pubmed-abs-sub-05
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-sub-05
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: 0.1651
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.4638 | 0.11 | 500 | 0.3890 |
| 0.363 | 0.21 | 1000 | 0.3040 |
| 0.3053 | 0.32 | 1500 | 0.2812 |
| 0.3157 | 0.43 | 2000 | 0.2569 |
| 0.2515 | 0.54 | 2500 | 0.2380 |
| 0.2484 | 0.64 | 3000 | 0.2222 |
| 0.2295 | 0.75 | 3500 | 0.2136 |
| 0.2343 | 0.86 | 4000 | 0.2017 |
| 0.2455 | 0.96 | 4500 | 0.1969 |
| 0.2037 | 1.07 | 5000 | 0.1989 |
| 0.173 | 1.18 | 5500 | 0.1909 |
| 0.166 | 1.28 | 6000 | 0.1918 |
| 0.1607 | 1.39 | 6500 | 0.1875 |
| 0.203 | 1.5 | 7000 | 0.1833 |
| 0.1709 | 1.61 | 7500 | 0.1798 |
| 0.1272 | 1.71 | 8000 | 0.1777 |
| 0.2037 | 1.82 | 8500 | 0.1751 |
| 0.1493 | 1.93 | 9000 | 0.1720 |
| 0.1306 | 2.03 | 9500 | 0.1744 |
| 0.142 | 2.14 | 10000 | 0.1734 |
| 0.1159 | 2.25 | 10500 | 0.1752 |
| 0.1099 | 2.35 | 11000 | 0.1723 |
| 0.1229 | 2.46 | 11500 | 0.1695 |
| 0.1209 | 2.57 | 12000 | 0.1666 |
| 0.1477 | 2.68 | 12500 | 0.1657 |
| 0.0984 | 2.78 | 13000 | 0.1656 |
| 0.1002 | 2.89 | 13500 | 0.1659 |
| 0.1183 | 3.0 | 14000 | 0.1651 |
### Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1
|