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bert-small-finetuned-cuad-full – AI Model by muhtasham | AlphaNeural AI
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muhtasham
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bert-small-finetuned-cuad-full
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transformers
pytorch
tensorboard
bert
question-answering
generated_from_trainer
cuad
apache-2.0
endpoints_compatible
us
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bert-small-finetuned-cuad-full
This model is a fine-tuned version of
google/bert_uncased_L-4_H-512_A-8
on the cuad dataset. It achieves the following results on the evaluation set:
Loss: 0.0274
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: 42
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
0.0323
1.0
47569
0.0280
0.0314
2.0
95138
0.0265
0.0276
3.0
142707
0.0274
Framework versions
Transformers 4.21.1
Pytorch 1.12.1+cu113
Datasets 2.4.0
Tokenizers 0.12.1
