robbert2809_flow / README.md
Tommert25's picture
End of training
da1811a
metadata
license: mit
base_model: pdelobelle/robbert-v2-dutch-base
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: robbert2809_flow
    results: []

robbert2809_flow

This model is a fine-tuned version of 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