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albert-xxlarge-v2-finetuned-csqa – AI Model by danlou | AlphaNeural AI | AlphaNeural AI
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albert-xxlarge-v2-finetuned-csqa
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transformers
pytorch
albert
multiple-choice
generated_from_trainer
commonsense_qa
apache-2.0
endpoints_compatible
us
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albert-xxlarge-v2-finetuned-csqa
This model is a fine-tuned version of
albert-xxlarge-v2
on the commonsense_qa dataset. It achieves the following results on the evaluation set:
Loss: 1.6177
Accuracy: 0.7871
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: 1e-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: 5
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.7464
1.0
609
0.5319
0.7985
0.3116
2.0
1218
0.6422
0.7936
0.0769
3.0
1827
1.2674
0.7952
0.0163
4.0
2436
1.4839
0.7903
0.0122
5.0
3045
1.6177
0.7871
Framework versions
Transformers 4.8.2
Pytorch 1.9.0
Datasets 1.10.2
Tokenizers 0.10.3
