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albert-base-qa-coQA-2-k-fold-1 – AI Model by mateiaass | AlphaNeural AI
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mateiaass
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albert-base-qa-coQA-2-k-fold-1
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transformers
pytorch
albert
question-answering
generated_from_trainer
albert/albert-base-v2
finetune
apache-2.0
endpoints_compatible
us
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albert-base-qa-coQA-2-k-fold-1
This model is a fine-tuned version of
albert-base-v2
on the None dataset. It achieves the following results on the evaluation set:
Loss: 2.7108
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
2.6589
1.0
5467
2.6679
2.3399
2.0
10934
2.6262
2.0179
3.0
16401
2.7108
Framework versions
Transformers 4.34.1
Pytorch 2.1.0+cu118
Datasets 2.14.6
Tokenizers 0.14.1
