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aristo-roberta-finetuned-csqa – AI Model by danlou | AlphaNeural AI
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danlou
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aristo-roberta-finetuned-csqa
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transformers
pytorch
roberta
multiple-choice
generated_from_trainer
commonsense_qa
mit
endpoints_compatible
us
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aristo-roberta-finetuned-csqa
This model is a fine-tuned version of
LIAMF-USP/aristo-roberta
on the commonsense_qa dataset. It achieves the following results on the evaluation set:
Loss: 1.2187
Accuracy: 0.7305
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
1.131
1.0
609
0.7109
0.7232
0.6957
2.0
1218
0.6912
0.7346
0.459
3.0
1827
0.8364
0.7305
0.3063
4.0
2436
1.0595
0.7322
0.2283
5.0
3045
1.2187
0.7305
Framework versions
Transformers 4.9.0
Pytorch 1.9.0
Datasets 1.10.2
Tokenizers 0.10.3
