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LR-1E4-Bert-QA-Pytorch-FULL – AI Model by tyavika | AlphaNeural AI
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LR-1E4-Bert-QA-Pytorch-FULL
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transformers
pytorch
bert
question-answering
generated_from_trainer
apache-2.0
endpoints_compatible
us
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LR-1E4-Bert-QA-Pytorch-FULL
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: 1.4978
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: 0.0001
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10
Training results
Training Loss
Epoch
Step
Validation Loss
1.307
1.0
3290
1.2050
0.947
2.0
6580
1.1626
0.6696
3.0
9870
1.2209
0.4711
4.0
13160
1.4978
Framework versions
Transformers 4.28.0
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3
