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---
license: apache-2.0
base_model: facebook/bart-base
tags:
- generated_from_trainer
model-index:
- name: pubmed-abs-sub-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-sub-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: 0.1503
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.3928 | 0.11 | 500 | 0.3528 |
| 0.3138 | 0.21 | 1000 | 0.2822 |
| 0.3223 | 0.32 | 1500 | 0.2444 |
| 0.3311 | 0.43 | 2000 | 0.2249 |
| 0.2256 | 0.54 | 2500 | 0.2169 |
| 0.222 | 0.64 | 3000 | 0.1999 |
| 0.2153 | 0.75 | 3500 | 0.1990 |
| 0.2167 | 0.86 | 4000 | 0.1814 |
| 0.2041 | 0.96 | 4500 | 0.1764 |
| 0.162 | 1.07 | 5000 | 0.1777 |
| 0.1645 | 1.18 | 5500 | 0.1742 |
| 0.1649 | 1.28 | 6000 | 0.1747 |
| 0.1721 | 1.39 | 6500 | 0.1660 |
| 0.1652 | 1.5 | 7000 | 0.1666 |
| 0.15 | 1.61 | 7500 | 0.1626 |
| 0.133 | 1.71 | 8000 | 0.1620 |
| 0.159 | 1.82 | 8500 | 0.1574 |
| 0.1415 | 1.93 | 9000 | 0.1558 |
| 0.1174 | 2.03 | 9500 | 0.1573 |
| 0.1226 | 2.14 | 10000 | 0.1562 |
| 0.1018 | 2.25 | 10500 | 0.1571 |
| 0.0978 | 2.35 | 11000 | 0.1550 |
| 0.0985 | 2.46 | 11500 | 0.1537 |
| 0.1284 | 2.57 | 12000 | 0.1507 |
| 0.1187 | 2.68 | 12500 | 0.1513 |
| 0.0806 | 2.78 | 13000 | 0.1516 |
| 0.1092 | 2.89 | 13500 | 0.1508 |
| 0.0996 | 3.0 | 14000 | 0.1503 |
### Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1
|