---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-bpmn
  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. -->

# bert-finetuned-bpmn

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2656
- Precision: 0.7314
- Recall: 0.8366
- F1: 0.7805
- Accuracy: 0.8939

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 10   | 0.8437          | 0.1899    | 0.3203 | 0.2384 | 0.7005   |
| No log        | 2.0   | 20   | 0.4967          | 0.5421    | 0.7582 | 0.6322 | 0.8417   |
| No log        | 3.0   | 30   | 0.3403          | 0.6719    | 0.8431 | 0.7478 | 0.8867   |
| No log        | 4.0   | 40   | 0.2821          | 0.6923    | 0.8235 | 0.7522 | 0.8903   |
| No log        | 5.0   | 50   | 0.2656          | 0.7314    | 0.8366 | 0.7805 | 0.8939   |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.7.1
- Tokenizers 0.13.2