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---
license: apache-2.0
base_model: facebook/bart-base
tags:
- generated_from_trainer
model-index:
- name: pubmed-abs-sub-01
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-01
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: 0.0931
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.2288 | 0.11 | 500 | 0.1670 |
| 0.1744 | 0.21 | 1000 | 0.1545 |
| 0.1726 | 0.32 | 1500 | 0.1341 |
| 0.1622 | 0.43 | 2000 | 0.1329 |
| 0.1382 | 0.54 | 2500 | 0.1289 |
| 0.1322 | 0.64 | 3000 | 0.1184 |
| 0.1288 | 0.75 | 3500 | 0.1182 |
| 0.1304 | 0.86 | 4000 | 0.1088 |
| 0.1255 | 0.96 | 4500 | 0.1068 |
| 0.1039 | 1.07 | 5000 | 0.1093 |
| 0.0969 | 1.18 | 5500 | 0.1060 |
| 0.1001 | 1.28 | 6000 | 0.1087 |
| 0.0966 | 1.39 | 6500 | 0.1027 |
| 0.101 | 1.5 | 7000 | 0.0999 |
| 0.0851 | 1.61 | 7500 | 0.1010 |
| 0.1068 | 1.71 | 8000 | 0.1021 |
| 0.1024 | 1.82 | 8500 | 0.0966 |
| 0.0852 | 1.93 | 9000 | 0.0962 |
| 0.0688 | 2.03 | 9500 | 0.0967 |
| 0.0791 | 2.14 | 10000 | 0.0987 |
| 0.0606 | 2.25 | 10500 | 0.0978 |
| 0.0732 | 2.35 | 11000 | 0.0963 |
| 0.0758 | 2.46 | 11500 | 0.0951 |
| 0.0765 | 2.57 | 12000 | 0.0945 |
| 0.0671 | 2.68 | 12500 | 0.0932 |
| 0.0422 | 2.78 | 13000 | 0.0936 |
| 0.0493 | 2.89 | 13500 | 0.0942 |
| 0.0542 | 3.0 | 14000 | 0.0931 |
### Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1
|