metadata

license: mit
base_model: DTAI-KULeuven/robbert-2023-dutch-base
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - accuracy
model-index:
  - name: robbert-2023-dutch-base-gender
    results: []

robbert-2023-dutch-base-gender

This model is a fine-tuned version of DTAI-KULeuven/robbert-2023-dutch-base on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.6591
Precision: 0.6282
Recall: 0.6290
Fscore: 0.6278
Accuracy: 0.6285

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: 1e-05
train_batch_size: 64
eval_batch_size: 64
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 1.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	Fscore	Accuracy
0.616	0.29	2000	0.6498	0.6295	0.6299	0.6266	0.6267
0.6033	0.59	4000	0.6584	0.6278	0.6274	0.6228	0.6228
0.5896	0.88	6000	0.6600	0.6285	0.6293	0.6282	0.6290

Framework versions

Transformers 4.36.2
Pytorch 2.1.2+cu121
Datasets 2.14.5
Tokenizers 0.15.0