bpmn-information-extraction-v2
This model is a fine-tuned version of bert-base-cased on a dataset containing 104 textual process descriptions.
The dataset and the training scripts can be found here: https://github.com/jtlicardo/process-visualizer/tree/main/src/token_classification
The dataset contains 5 target labels:
AGENT
TASK
TASK_INFO
PROCESS_INFO
CONDITION
It achieves the following results on the evaluation set:
- Loss: 0.2179
- Precision: 0.8826
- Recall: 0.9246
- F1: 0.9031
- Accuracy: 0.9516
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: 2e-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: 15
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
1.9945 | 1.0 | 12 | 1.5128 | 0.2534 | 0.3730 | 0.3018 | 0.5147 |
1.2161 | 2.0 | 24 | 0.8859 | 0.2977 | 0.4524 | 0.3591 | 0.7256 |
0.6755 | 3.0 | 36 | 0.4876 | 0.5562 | 0.7262 | 0.6299 | 0.8604 |
0.372 | 4.0 | 48 | 0.3091 | 0.7260 | 0.8413 | 0.7794 | 0.9128 |
0.2412 | 5.0 | 60 | 0.2247 | 0.7526 | 0.8571 | 0.8015 | 0.9342 |
0.1636 | 6.0 | 72 | 0.2102 | 0.8043 | 0.8968 | 0.8480 | 0.9413 |
0.1325 | 7.0 | 84 | 0.1910 | 0.8667 | 0.9286 | 0.8966 | 0.9500 |
0.11 | 8.0 | 96 | 0.2352 | 0.8456 | 0.9127 | 0.8779 | 0.9389 |
0.0945 | 9.0 | 108 | 0.2179 | 0.8550 | 0.9127 | 0.8829 | 0.9429 |
0.0788 | 10.0 | 120 | 0.2203 | 0.8830 | 0.9286 | 0.9052 | 0.9445 |
0.0721 | 11.0 | 132 | 0.2079 | 0.8902 | 0.9325 | 0.9109 | 0.9516 |
0.0617 | 12.0 | 144 | 0.2367 | 0.8797 | 0.9286 | 0.9035 | 0.9445 |
0.0615 | 13.0 | 156 | 0.2183 | 0.8859 | 0.9246 | 0.9049 | 0.9492 |
0.0526 | 14.0 | 168 | 0.2179 | 0.8826 | 0.9246 | 0.9031 | 0.9516 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.0
- Tokenizers 0.13.2
- Downloads last month
- 699
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for jtlicardo/bpmn-information-extraction-v2
Base model
google-bert/bert-base-cased