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chtn_bert_qa_model – AI Model by Chetna19 | AlphaNeural AI
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Chetna19
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chtn_bert_qa_model
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transformers
pytorch
tensorboard
bert
question-answering
generated_from_trainer
subjqa
cc-by-4.0
endpoints_compatible
us
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chtn_bert_qa_model
This model is a fine-tuned version of
deepset/bert-base-cased-squad2
on the subjqa dataset. It achieves the following results on the evaluation set:
Loss: 3.2773
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: 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: 5
Training results
Training Loss
Epoch
Step
Validation Loss
No log
1.0
32
2.8350
No log
2.0
64
2.8860
No log
3.0
96
3.1081
No log
4.0
128
3.2405
No log
5.0
160
3.2773
Framework versions
Transformers 4.26.1
Pytorch 1.13.1+cu116
Datasets 2.10.1
Tokenizers 0.13.2
