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bert-complexity-scorer – AI Model by tcma | AlphaNeural AI
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tcma
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bert-complexity-scorer
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transformers
safetensors
bert
text-classification
generated_from_trainer
google-bert/bert-base-uncased
finetune
apache-2.0
endpoints_compatible
us
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bert-complexity-scorer
This model is a fine-tuned version of
google-bert/bert-base-uncased
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.6044
Accuracy: 0.8239
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: 2
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 8
optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
4.2220
1.0
822
0.5959
0.7979
1.9274
2.0
1644
0.5869
0.8166
1.5170
3.0
2466
0.6044
0.8239
Framework versions
Transformers 5.12.1
Pytorch 2.12.0+cu130
Datasets 5.0.0
Tokenizers 0.22.2
