---
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: 0.4378
- Precision: 0.7075
- Recall: 0.7311
- F1: 0.7191
- Accuracy: 0.8758

## 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: 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  | 0.5027          | 0.6506    | 0.6860 | 0.6678 | 0.8551   |
| No log        | 2.0   | 236  | 0.4378          | 0.7075    | 0.7311 | 0.7191 | 0.8758   |
| No log        | 3.0   | 354  | 0.4974          | 0.7279    | 0.7335 | 0.7307 | 0.8725   |
| No log        | 4.0   | 472  | 0.5225          | 0.7417    | 0.7469 | 0.7443 | 0.8723   |
| 0.3483        | 5.0   | 590  | 0.5488          | 0.7662    | 0.7335 | 0.7495 | 0.8789   |
| 0.3483        | 6.0   | 708  | 0.5439          | 0.7749    | 0.7645 | 0.7697 | 0.8861   |
| 0.3483        | 7.0   | 826  | 0.5673          | 0.7676    | 0.7663 | 0.7669 | 0.8838   |
| 0.3483        | 8.0   | 944  | 0.5820          | 0.7744    | 0.7680 | 0.7712 | 0.8850   |


### Framework versions

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