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bert-base-uncased-supreme-court-32batch – AI Model by annabellehuether | AlphaNeural AI
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bert-base-uncased-supreme-court-32batch
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transformers
tensorboard
safetensors
bert
text-classification
generated_from_trainer
google-bert/bert-base-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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bert-base-uncased-supreme-court-32batch
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: 0.6089
Accuracy: 0.6607
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: 32
eval_batch_size: 32
seed: 7
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.6428
1.0
660
0.5527
0.6456
0.6006
2.0
1320
0.5647
0.6574
0.5602
3.0
1980
0.6089
0.6607
Framework versions
Transformers 4.35.1
Pytorch 2.1.0+cu121
Datasets 2.14.6
Tokenizers 0.14.1
