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bert-base-uncased-finetuned-wnli – AI Model by Sumaia | AlphaNeural AI
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Sumaia
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bert-base-uncased-finetuned-wnli
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transformers
pytorch
bert
text-classification
generated_from_trainer
glue
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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bert-base-uncased-finetuned-wnli
This model is a fine-tuned version of
bert-base-uncased
on the glue dataset. It achieves the following results on the evaluation set:
Loss: 0.6913
Accuracy: 0.5634
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: 128
eval_batch_size: 128
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
No log
1.0
73
0.7008
0.4366
No log
2.0
146
0.6943
0.5211
No log
3.0
219
0.6943
0.4789
No log
4.0
292
0.6913
0.5634
No log
5.0
365
0.6932
0.5634
Framework versions
Transformers 4.26.1
Pytorch 1.13.1+cpu
Datasets 2.10.1
Tokenizers 0.13.2
