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roberta-base-detect-dep – AI Model by Trong-Nghia | AlphaNeural AI
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Trong-Nghia
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roberta-base-detect-dep
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transformers
pytorch
tensorboard
roberta
text-classification
generated_from_trainer
mit
autotrain_compatible
endpoints_compatible
us
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roberta-base-detect-dep
This model is a fine-tuned version of
roberta-base
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.5281
Accuracy: 0.755
F1: 0.8251
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: 5e-06
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: 2
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
No log
1.0
376
0.5435
0.741
0.8198
0.6199
2.0
752
0.5281
0.755
0.8251
Framework versions
Transformers 4.30.2
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3
