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bpmn-task-extractor
This model is a fine-tuned version of 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
