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---
license: apache-2.0
base_model: facebook/bart-base
tags:
- generated_from_trainer
model-index:
- name: pubmed-abs-sub-03
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-03
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: 0.1366
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.3549 | 0.11 | 500 | 0.3112 |
| 0.2635 | 0.21 | 1000 | 0.2464 |
| 0.2497 | 0.32 | 1500 | 0.2210 |
| 0.2762 | 0.43 | 2000 | 0.2121 |
| 0.2265 | 0.54 | 2500 | 0.1923 |
| 0.1911 | 0.64 | 3000 | 0.1813 |
| 0.1629 | 0.75 | 3500 | 0.1777 |
| 0.1897 | 0.86 | 4000 | 0.1660 |
| 0.1782 | 0.96 | 4500 | 0.1617 |
| 0.1483 | 1.07 | 5000 | 0.1648 |
| 0.1412 | 1.18 | 5500 | 0.1592 |
| 0.1391 | 1.28 | 6000 | 0.1582 |
| 0.144 | 1.39 | 6500 | 0.1506 |
| 0.1524 | 1.5 | 7000 | 0.1509 |
| 0.1127 | 1.61 | 7500 | 0.1505 |
| 0.1224 | 1.71 | 8000 | 0.1470 |
| 0.1504 | 1.82 | 8500 | 0.1419 |
| 0.1123 | 1.93 | 9000 | 0.1407 |
| 0.0964 | 2.03 | 9500 | 0.1441 |
| 0.1045 | 2.14 | 10000 | 0.1428 |
| 0.1001 | 2.25 | 10500 | 0.1423 |
| 0.0842 | 2.35 | 11000 | 0.1416 |
| 0.085 | 2.46 | 11500 | 0.1407 |
| 0.1092 | 2.57 | 12000 | 0.1386 |
| 0.11 | 2.68 | 12500 | 0.1376 |
| 0.0769 | 2.78 | 13000 | 0.1370 |
| 0.084 | 2.89 | 13500 | 0.1373 |
| 0.0833 | 3.0 | 14000 | 0.1366 |
### Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1
|