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bert_qa_model – AI Model by KienLe21 | AlphaNeural AI
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KienLe21
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bert_qa_model
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transformers
tensorboard
safetensors
distilbert
question-answering
generated_from_trainer
distilbert/distilbert-base-uncased
finetune
apache-2.0
endpoints_compatible
us
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bert_qa_model
This model is a fine-tuned version of
distilbert-base-uncased
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 3.3622
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: 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
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
No log
1.0
100
3.7338
No log
2.0
200
3.4543
No log
3.0
300
3.3622
Framework versions
Transformers 4.48.3
Pytorch 2.5.1+cu124
Datasets 3.3.1
Tokenizers 0.21.0
