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distilbert-qa – AI Model by V1G1L | AlphaNeural AI
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V1G1L
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distilbert-qa
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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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distilbert-qa
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: 1.5547
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: 3e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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
125
2.1237
No log
2.0
250
1.6052
No log
3.0
375
1.5547
Framework versions
Transformers 4.57.6
Pytorch 2.9.1+cu128
Datasets 2.21.0
Tokenizers 0.22.2
