---
license: mit
base_model: pdelobelle/robbert-v2-dutch-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: robbert2809_flow
  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. -->

# robbert2809_flow

This model is a fine-tuned version of [pdelobelle/robbert-v2-dutch-base](https://huggingface.co/pdelobelle/robbert-v2-dutch-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3597
- Precision: 0.7239
- Recall: 0.7197
- F1: 0.7218
- Accuracy: 0.8938

## 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: 2.5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 118  | 0.4622          | 0.6165    | 0.5828 | 0.5992 | 0.8584   |
| No log        | 2.0   | 236  | 0.4044          | 0.6675    | 0.6620 | 0.6647 | 0.8772   |
| No log        | 3.0   | 354  | 0.3787          | 0.6945    | 0.7220 | 0.708  | 0.8904   |
| No log        | 4.0   | 472  | 0.3597          | 0.7239    | 0.7197 | 0.7218 | 0.8938   |
| 0.4344        | 5.0   | 590  | 0.3615          | 0.7273    | 0.7430 | 0.7351 | 0.8974   |
| 0.4344        | 6.0   | 708  | 0.3909          | 0.7410    | 0.7418 | 0.7414 | 0.8977   |
| 0.4344        | 7.0   | 826  | 0.3868          | 0.7394    | 0.7343 | 0.7368 | 0.8966   |
| 0.4344        | 8.0   | 944  | 0.3858          | 0.7402    | 0.7389 | 0.7396 | 0.8977   |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3