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bert_large_subjqa_model – AI Model by Chetna19 | AlphaNeural AI
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Chetna19
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bert_large_subjqa_model
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transformers
pytorch
tensorboard
bert
question-answering
generated_from_trainer
apache-2.0
endpoints_compatible
us
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bert_large_subjqa_model
This model is a fine-tuned version of
bert-large-uncased-whole-word-masking-finetuned-squad
on the None dataset. It achieves the following results on the evaluation set:
Loss: 4.5694
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
205
2.6886
No log
2.0
410
3.0812
1.3352
3.0
615
3.6959
1.3352
4.0
820
4.2810
0.5176
5.0
1025
4.5694
Framework versions
Transformers 4.28.0
Pytorch 1.13.0a0+d321be6
Datasets 2.12.0
Tokenizers 0.13.3
