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bert-qa-squad – AI Model by bhatia1289 | AlphaNeural AI
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bert-qa-squad
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transformers
safetensors
bert
question-answering
generated_from_trainer
google-bert/bert-base-uncased
finetune
apache-2.0
endpoints_compatible
us
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bert-qa-squad
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: 4.2056
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: 8
eval_batch_size: 8
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
training_steps: 100
Training results
Training Loss
Epoch
Step
Validation Loss
4.2343
0.0090
100
4.2056
Framework versions
Transformers 4.49.0
Pytorch 2.6.0+cu126
Datasets 3.3.1
Tokenizers 0.21.0
