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---
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: cause-bert-biocause
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. -->
# cause-bert-biocause
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4364
- Precision: 0.1647
- Recall: 0.3459
- F1: 0.2231
- Accuracy: 0.8160
- Cause P: 0.1647
- Cause R: 0.3459
- Cause F1: 0.2231
## 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | Cause P | Cause R | Cause F1 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|:-------:|:-------:|:--------:|
| 0.6498 | 0.25 | 20 | 0.6248 | 0.0544 | 0.1698 | 0.0824 | 0.7705 | 0.0544 | 0.1698 | 0.0824 |
| 0.6498 | 0.5 | 40 | 0.5229 | 0.0532 | 0.1572 | 0.0795 | 0.6600 | 0.0532 | 0.1572 | 0.0795 |
| 0.6498 | 0.75 | 60 | 0.4613 | 0.1190 | 0.2327 | 0.1574 | 0.8274 | 0.1190 | 0.2327 | 0.1574 |
| 0.6498 | 1.0 | 80 | 0.4376 | 0.1460 | 0.2956 | 0.1954 | 0.8145 | 0.1460 | 0.2956 | 0.1954 |
| 0.6498 | 1.25 | 100 | 0.4660 | 0.1829 | 0.2956 | 0.2260 | 0.8312 | 0.1829 | 0.2956 | 0.2260 |
| 0.6498 | 1.5 | 120 | 0.4523 | 0.1902 | 0.3899 | 0.2557 | 0.8148 | 0.1902 | 0.3899 | 0.2557 |
| 0.6498 | 1.75 | 140 | 0.4414 | 0.1756 | 0.3711 | 0.2384 | 0.8138 | 0.1756 | 0.3711 | 0.2384 |
| 0.6498 | 2.0 | 160 | 0.4364 | 0.1647 | 0.3459 | 0.2231 | 0.8160 | 0.1647 | 0.3459 | 0.2231 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.3.1.post100
- Datasets 2.20.0
- Tokenizers 0.15.1
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