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MLG – AI Model by JorgeUDG | AlphaNeural AI
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JorgeUDG
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MLG
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transformers
pytorch
distilbert
question-answering
generated_from_trainer
squad
distilbert/distilbert-base-uncased
finetune
apache-2.0
endpoints_compatible
us
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MLG
This model is a fine-tuned version of
distilbert-base-uncased
on the squad dataset. It achieves the following results on the evaluation set:
Loss: 1.7901
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: 3
Training results
Training Loss
Epoch
Step
Validation Loss
No log
1.0
250
2.3306
2.744
2.0
500
1.8785
2.744
3.0
750
1.7901
Framework versions
Transformers 4.34.1
Pytorch 2.1.0+cu118
Datasets 2.14.6
Tokenizers 0.14.1