metadata
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: []
relation-bert-biocause
This model is a fine-tuned version of 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