| | --- |
| | license: mit |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - precision |
| | - recall |
| | - f1 |
| | - accuracy |
| | model-index: |
| | - name: bpmn-task-extractor |
| | 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. --> |
| |
|
| | # bpmn-task-extractor |
| |
|
| | This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.0970 |
| | - Precision: 0.95 |
| | - Recall: 0.95 |
| | - F1: 0.9500 |
| | - Accuracy: 0.9888 |
| |
|
| | ## 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: 5e-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: 10 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | | No log | 1.0 | 1 | 1.0813 | 0.3077 | 0.2 | 0.2424 | 0.6404 | |
| | | No log | 2.0 | 2 | 0.7296 | 0.4783 | 0.55 | 0.5116 | 0.7191 | |
| | | No log | 3.0 | 3 | 0.5097 | 0.6111 | 0.55 | 0.5789 | 0.8090 | |
| | | No log | 4.0 | 4 | 0.3683 | 0.7059 | 0.6 | 0.6486 | 0.8652 | |
| | | No log | 5.0 | 5 | 0.2926 | 0.75 | 0.6 | 0.6667 | 0.8539 | |
| | | No log | 6.0 | 6 | 0.2268 | 0.7647 | 0.65 | 0.7027 | 0.8764 | |
| | | No log | 7.0 | 7 | 0.1699 | 0.7778 | 0.7 | 0.7368 | 0.9101 | |
| | | No log | 8.0 | 8 | 0.1273 | 0.8 | 0.8 | 0.8000 | 0.9438 | |
| | | No log | 9.0 | 9 | 0.1061 | 0.95 | 0.95 | 0.9500 | 0.9888 | |
| | | No log | 10.0 | 10 | 0.0970 | 0.95 | 0.95 | 0.9500 | 0.9888 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.21.3 |
| | - Pytorch 1.12.1+cu113 |
| | - Datasets 2.4.0 |
| | - Tokenizers 0.12.1 |
| |
|
