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qna – AI Model by flopaflop | AlphaNeural AI
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qna
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transformers
safetensors
distilbert
question-answering
generated_from_trainer
distilbert/distilbert-base-uncased
finetune
apache-2.0
endpoints_compatible
us
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qna
This model is a fine-tuned version of
distilbert/distilbert-base-uncased
on an unknown dataset.
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: 1
Training results
Training Loss
Epoch
Step
Validation Loss
No log
1.0
250
3.0101
Framework versions
Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.1.0
Tokenizers 0.21.0
