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bert – AI Model by 202k | AlphaNeural AI
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202k
/
bert
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transformers
pytorch
tensorboard
bert
text-classification
generated_from_trainer
apache-2.0
autotrain_compatible
endpoints_compatible
us
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Model card
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bert
This model is a fine-tuned version of
bert-base-uncased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.6959
Accuracy: 0.5263
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: 10
eval_batch_size: 10
seed: 0
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
1
0.6980
0.4737
No log
2.0
2
0.6968
0.4737
No log
3.0
3
0.6960
0.4737
No log
4.0
4
0.6958
0.4474
No log
5.0
5
0.6959
0.5263
Framework versions
Transformers 4.27.3
Pytorch 1.13.1+cu116
Datasets 2.10.1
Tokenizers 0.13.2
