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---
license: apache-2.0
base_model: facebook/bart-base
tags:
- generated_from_trainer
model-index:
- name: pubmed-abs-sub-02
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-02
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: 0.1162
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.2641 | 0.11 | 500 | 0.2493 |
| 0.2369 | 0.21 | 1000 | 0.1986 |
| 0.2348 | 0.32 | 1500 | 0.1810 |
| 0.2239 | 0.43 | 2000 | 0.1732 |
| 0.1745 | 0.54 | 2500 | 0.1643 |
| 0.1664 | 0.64 | 3000 | 0.1493 |
| 0.1701 | 0.75 | 3500 | 0.1446 |
| 0.2041 | 0.86 | 4000 | 0.1375 |
| 0.1541 | 0.96 | 4500 | 0.1347 |
| 0.1168 | 1.07 | 5000 | 0.1398 |
| 0.1174 | 1.18 | 5500 | 0.1339 |
| 0.1108 | 1.28 | 6000 | 0.1345 |
| 0.1163 | 1.39 | 6500 | 0.1292 |
| 0.1292 | 1.5 | 7000 | 0.1268 |
| 0.0999 | 1.61 | 7500 | 0.1270 |
| 0.1023 | 1.71 | 8000 | 0.1225 |
| 0.123 | 1.82 | 8500 | 0.1208 |
| 0.1105 | 1.93 | 9000 | 0.1182 |
| 0.0938 | 2.03 | 9500 | 0.1212 |
| 0.0995 | 2.14 | 10000 | 0.1215 |
| 0.075 | 2.25 | 10500 | 0.1223 |
| 0.0746 | 2.35 | 11000 | 0.1201 |
| 0.0816 | 2.46 | 11500 | 0.1187 |
| 0.0819 | 2.57 | 12000 | 0.1170 |
| 0.0876 | 2.68 | 12500 | 0.1164 |
| 0.0628 | 2.78 | 13000 | 0.1168 |
| 0.0695 | 2.89 | 13500 | 0.1166 |
| 0.0835 | 3.0 | 14000 | 0.1162 |
### Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1
|