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roberta-base-finetuned-mrpc – AI Model by VitaliiVrublevskyi | AlphaNeural AI
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VitaliiVrublevskyi
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roberta-base-finetuned-mrpc
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transformers
pytorch
tensorboard
roberta
text-classification
generated_from_trainer
glue
mit
model-index
autotrain_compatible
endpoints_compatible
us
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roberta-base-finetuned-mrpc
This model is a fine-tuned version of
roberta-base
on the glue dataset. It achieves the following results on the evaluation set:
Loss: 0.3055
Accuracy: 0.8799
F1: 0.9104
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: 32
seed: 60
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
Accuracy
F1
No log
1.0
115
0.3613
0.8529
0.8889
No log
2.0
230
0.2917
0.8848
0.9147
No log
3.0
345
0.3055
0.8799
0.9104
Framework versions
Transformers 4.28.0
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.13.3
