---
base_model: dmis-lab/biobert-base-cased-v1.2
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: relation-biobert-biocause
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# relation-biobert-biocause

This model is a fine-tuned version of [dmis-lab/biobert-base-cased-v1.2](https://huggingface.co/dmis-lab/biobert-base-cased-v1.2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2103
- Precision: 0.1164
- Recall: 0.625
- F1: 0.1963
- Accuracy: 0.9448
- Relation P: 0.1164
- Relation R: 0.625
- Relation F1: 0.1963

## 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 |
|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|:----------:|:----------:|:-----------:|
| 0.6563        | 0.1282 | 20   | 0.2984          | 0.0211    | 0.2105 | 0.0384 | 0.8265   | 0.0211     | 0.2105     | 0.0384      |
| 0.6563        | 0.2564 | 40   | 0.2302          | 0.0763    | 0.4605 | 0.1308 | 0.9266   | 0.0763     | 0.4605     | 0.1308      |
| 0.6563        | 0.3846 | 60   | 0.4003          | 0.1406    | 0.5921 | 0.2273 | 0.9617   | 0.1406     | 0.5921     | 0.2273      |
| 0.6563        | 0.5128 | 80   | 0.2185          | 0.0554    | 0.4671 | 0.0990 | 0.8933   | 0.0554     | 0.4671     | 0.0990      |
| 0.6563        | 0.6410 | 100  | 0.2261          | 0.1345    | 0.7105 | 0.2262 | 0.9510   | 0.1345     | 0.7105     | 0.2262      |
| 0.6563        | 0.7692 | 120  | 0.2315          | 0.1259    | 0.6579 | 0.2114 | 0.9502   | 0.1259     | 0.6579     | 0.2114      |
| 0.6563        | 0.8974 | 140  | 0.2324          | 0.1417    | 0.6711 | 0.2339 | 0.9547   | 0.1417     | 0.6711     | 0.2339      |


### Framework versions

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