---
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: relation-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. -->

# relation-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: 0.2130
- Precision: 0.1019
- Recall: 0.5855
- F1: 0.1737
- Accuracy: 0.9399
- Relation P: 0.1019
- Relation R: 0.5855
- Relation F1: 0.1737

## 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: 4e-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: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Precision | Recall | F1     | Accuracy | Relation P | Relation R | Relation F1 |
|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|:----------:|:----------:|:-----------:|
| 0.7103        | 0.1282 | 20   | 0.3074          | 0.0214    | 0.2368 | 0.0392 | 0.8048   | 0.0214     | 0.2368     | 0.0392      |
| 0.7103        | 0.2564 | 40   | 0.2230          | 0.0523    | 0.3882 | 0.0922 | 0.8985   | 0.0523     | 0.3882     | 0.0922      |
| 0.7103        | 0.3846 | 60   | 0.2568          | 0.0983    | 0.5987 | 0.1688 | 0.9413   | 0.0983     | 0.5987     | 0.1688      |
| 0.7103        | 0.5128 | 80   | 0.2166          | 0.0593    | 0.4671 | 0.1053 | 0.9000   | 0.0593     | 0.4671     | 0.1053      |
| 0.7103        | 0.6410 | 100  | 0.2308          | 0.1240    | 0.6842 | 0.2099 | 0.9489   | 0.1240     | 0.6842     | 0.2099      |
| 0.7103        | 0.7692 | 120  | 0.2246          | 0.1080    | 0.625  | 0.1841 | 0.9435   | 0.1080     | 0.625      | 0.1841      |
| 0.7103        | 0.8974 | 140  | 0.2290          | 0.1196    | 0.6316 | 0.2010 | 0.9483   | 0.1196     | 0.6316     | 0.2010      |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1