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m_bert_large_qa_model_1 – AI Model by Chetna19 | AlphaNeural AI
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Chetna19
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m_bert_large_qa_model_1
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transformers
pytorch
tensorboard
bert
question-answering
generated_from_trainer
subjqa
apache-2.0
endpoints_compatible
us
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m_bert_large_qa_model_1
This model is a fine-tuned version of
bert-large-uncased-whole-word-masking-finetuned-squad
on the subjqa dataset. It achieves the following results on the evaluation set:
Loss: 5.9072
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
4.8490
No log
2.0
64
5.0067
No log
3.0
96
5.5756
No log
4.0
128
5.8065
No log
5.0
160
5.9072
Framework versions
Transformers 4.28.0
Pytorch 1.13.0a0+d321be6
Datasets 2.12.0
Tokenizers 0.13.3
