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diff_model – AI Model by radyad | AlphaNeural AI
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diff_model
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transformers
pytorch
tensorboard
bert
question-answering
generated_from_trainer
mlqa
endpoints_compatible
us
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diff_model
This model is a fine-tuned version of
huggingface-course/bert-finetuned-squad
on the mlqa dataset. It achieves the following results on the evaluation set:
Loss: 1.1014
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
355
0.8941
0.931
2.0
710
0.9768
0.4794
3.0
1065
1.1014
Framework versions
Transformers 4.30.2
Pytorch 2.0.1+cu118
Datasets 2.13.0
Tokenizers 0.13.3
