readme: ---
  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
  