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albert_base_v2_dropout – AI Model by hkonsg | AlphaNeural AI
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hkonsg
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albert_base_v2_dropout
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transformers
pytorch
tensorboard
albert
question-answering
generated_from_trainer
squad_v2
apache-2.0
endpoints_compatible
us
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albert_base_v2_dropout
This model is a fine-tuned version of
albert-base-v2
on the squad_v2 dataset. It achieves the following results on the evaluation set:
Loss: 0.9244
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
1.462
1.0
8248
1.7943
0.8841
2.0
16496
0.9586
0.7636
3.0
24744
0.9244
Framework versions
Transformers 4.25.1
Pytorch 1.13.0+cu116
Datasets 2.7.1
Tokenizers 0.13.2
