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BertjeWDialDataALL – AI Model by Jeska | AlphaNeural AI
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Jeska
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BertjeWDialDataALL
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transformers
pytorch
tensorboard
bert
fill-mask
generated_from_trainer
autotrain_compatible
endpoints_compatible
us
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BertjeWDialDataALL
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: 1.9469
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: 2e-05
train_batch_size: 16
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 8.0
Training results
Training Loss
Epoch
Step
Validation Loss
2.1739
1.0
1542
2.0150
2.0759
2.0
3084
1.9918
2.0453
3.0
4626
2.0132
1.9936
4.0
6168
1.9341
1.9659
5.0
7710
1.9140
1.9545
6.0
9252
1.9418
1.9104
7.0
10794
1.9179
1.8991
8.0
12336
1.9157
Framework versions
Transformers 4.13.0.dev0
Pytorch 1.10.0
Datasets 1.16.1
Tokenizers 0.10.3
