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bert-large-e2-version2-noweight – AI Model by YanJiangJerry | AlphaNeural AI
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bert-large-e2-version2-noweight
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transformers
pytorch
bert
text-classification
generated_from_trainer
google-bert/bert-large-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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bert-large-e2-version2-noweight
This model is a fine-tuned version of
bert-large-uncased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.5193
Accuracy: 0.9336
F1: 0.8269
Precision: 0.8039
Recall: 0.8512
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: 4
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
Precision
Recall
0.0645
1.0
4089
0.8181
0.8762
0.7398
0.6080
0.9446
0.0123
2.0
8178
0.5193
0.9336
0.8269
0.8039
0.8512
Framework versions
Transformers 4.31.0
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3
