---
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