|
|
--- |
|
|
license: apache-2.0 |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
model-index: |
|
|
- name: DISO_bsc_test16 |
|
|
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. --> |
|
|
|
|
|
# DISO_bsc_test16 |
|
|
|
|
|
This model is a fine-tuned version of [PlanTL-GOB-ES/bsc-bio-ehr-es](https://huggingface.co/PlanTL-GOB-ES/bsc-bio-ehr-es) on the None dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 0.1732 |
|
|
- Diso Precision: 0.7577 |
|
|
- Diso Recall: 0.7757 |
|
|
- Diso F1: 0.7666 |
|
|
- Diso Number: 4552 |
|
|
- Overall Precision: 0.7577 |
|
|
- Overall Recall: 0.7757 |
|
|
- Overall F1: 0.7666 |
|
|
- Overall Accuracy: 0.9732 |
|
|
|
|
|
## 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: 8e-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 |
|
|
- num_epochs: 8 |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Diso Precision | Diso Recall | Diso F1 | Diso Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy | |
|
|
|:-------------:|:-----:|:-----:|:---------------:|:--------------:|:-----------:|:-------:|:-----------:|:-----------------:|:--------------:|:----------:|:----------------:| |
|
|
| 0.0948 | 1.0 | 1400 | 0.0766 | 0.7157 | 0.7594 | 0.7369 | 4552 | 0.7157 | 0.7594 | 0.7369 | 0.9710 | |
|
|
| 0.0631 | 2.0 | 2800 | 0.0818 | 0.7442 | 0.7599 | 0.7520 | 4552 | 0.7442 | 0.7599 | 0.7520 | 0.9726 | |
|
|
| 0.0454 | 3.0 | 4200 | 0.0842 | 0.7544 | 0.7654 | 0.7599 | 4552 | 0.7544 | 0.7654 | 0.7599 | 0.9728 | |
|
|
| 0.0311 | 4.0 | 5600 | 0.1113 | 0.7678 | 0.7700 | 0.7689 | 4552 | 0.7678 | 0.7700 | 0.7689 | 0.9732 | |
|
|
| 0.0217 | 5.0 | 7000 | 0.1231 | 0.7745 | 0.7687 | 0.7716 | 4552 | 0.7745 | 0.7687 | 0.7716 | 0.9743 | |
|
|
| 0.015 | 6.0 | 8400 | 0.1482 | 0.7651 | 0.7733 | 0.7691 | 4552 | 0.7651 | 0.7733 | 0.7691 | 0.9735 | |
|
|
| 0.0101 | 7.0 | 9800 | 0.1498 | 0.7576 | 0.7709 | 0.7642 | 4552 | 0.7576 | 0.7709 | 0.7642 | 0.9730 | |
|
|
| 0.0073 | 8.0 | 11200 | 0.1732 | 0.7577 | 0.7757 | 0.7666 | 4552 | 0.7577 | 0.7757 | 0.7666 | 0.9732 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.25.1 |
|
|
- Pytorch 1.13.0+cu116 |
|
|
- Datasets 2.8.0 |
|
|
- Tokenizers 0.13.2 |
|
|
|
