|
--- |
|
license: apache-2.0 |
|
base_model: facebook/bart-base |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: pubmed-abs-ins-con-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-ins-con-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: 0.0594 |
|
|
|
## 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 | |
|
|:-------------:|:-----:|:-----:|:---------------:| |
|
| 0.1805 | 0.11 | 500 | 0.1197 | |
|
| 0.1078 | 0.21 | 1000 | 0.0990 | |
|
| 0.126 | 0.32 | 1500 | 0.0879 | |
|
| 0.1501 | 0.43 | 2000 | 0.0806 | |
|
| 0.0957 | 0.54 | 2500 | 0.0849 | |
|
| 0.1111 | 0.64 | 3000 | 0.0765 | |
|
| 0.0942 | 0.75 | 3500 | 0.0785 | |
|
| 0.0897 | 0.86 | 4000 | 0.0703 | |
|
| 0.0867 | 0.96 | 4500 | 0.0701 | |
|
| 0.0838 | 1.07 | 5000 | 0.0711 | |
|
| 0.0757 | 1.18 | 5500 | 0.0673 | |
|
| 0.0586 | 1.28 | 6000 | 0.0759 | |
|
| 0.0701 | 1.39 | 6500 | 0.0648 | |
|
| 0.0655 | 1.5 | 7000 | 0.0652 | |
|
| 0.0569 | 1.61 | 7500 | 0.0667 | |
|
| 0.0564 | 1.71 | 8000 | 0.0650 | |
|
| 0.1031 | 1.82 | 8500 | 0.0631 | |
|
| 0.0701 | 1.93 | 9000 | 0.0590 | |
|
| 0.0612 | 2.03 | 9500 | 0.0625 | |
|
| 0.0576 | 2.14 | 10000 | 0.0627 | |
|
| 0.048 | 2.25 | 10500 | 0.0617 | |
|
| 0.044 | 2.35 | 11000 | 0.0616 | |
|
| 0.0459 | 2.46 | 11500 | 0.0605 | |
|
| 0.0546 | 2.57 | 12000 | 0.0588 | |
|
| 0.0533 | 2.68 | 12500 | 0.0589 | |
|
| 0.0354 | 2.78 | 13000 | 0.0592 | |
|
| 0.0366 | 2.89 | 13500 | 0.0606 | |
|
| 0.0436 | 3.0 | 14000 | 0.0594 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.34.1 |
|
- Pytorch 2.1.0 |
|
- Datasets 2.14.7 |
|
- Tokenizers 0.14.1 |
|
|
