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albert-base-v2-mrpc – AI Model by Alireza1044 | AlphaNeural AI
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albert-base-v2-mrpc
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transformers
pytorch
tensorboard
albert
text-classification
generated_from_trainer
en
glue
apache-2.0
autotrain_compatible
endpoints_compatible
us
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mrpc
This model is a fine-tuned version of
albert-base-v2
on the GLUE MRPC dataset. It achieves the following results on the evaluation set:
Loss: 0.4171
Accuracy: 0.8627
F1: 0.9011
Combined Score: 0.8819
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: 32
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 4.0
Training results
Framework versions
Transformers 4.9.0
Pytorch 1.9.0+cu102
Datasets 1.10.2
Tokenizers 0.10.3
