bert-hoofdthemas – AI Model by maretamasaeva | AlphaNeural AI

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maretamasaeva/
bert-hoofdthemas

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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bert-hoofdthemas

This model is a fine-tuned version of GroNLP/bert-base-dutch-cased on the None dataset. It achieves the following results on the evaluation set:

Loss: 1.1925
Accuracy: 0.7327

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: 0.0001
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 6

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.0712	1.0	2107	0.9968	0.7035
0.8567	2.0	4214	0.9297	0.7230
0.6865	3.0	6321	0.9586	0.7346
0.5546	4.0	8428	0.9767	0.7387
0.4429	5.0	10535	1.0708	0.7370
0.3395	6.0	12642	1.1925	0.7327

Framework versions

Transformers 4.21.3
Pytorch 1.12.1+cu113
Datasets 2.4.0
Tokenizers 0.12.1