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roberta-base-finetuned-classification – AI Model by ThomasLI | AlphaNeural AI
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ThomasLI
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roberta-base-finetuned-classification
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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-finetuned-classification
This model is a fine-tuned version of
roberta-base
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.3212
Accuracy: 0.8725
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
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
No log
1.0
200
0.3870
0.8287
No log
2.0
400
0.3212
0.8725
0.3583
3.0
600
0.3910
0.86
0.3583
4.0
800
0.6661
0.8237
0.1495
5.0
1000
0.7024
0.8213
Framework versions
Transformers 4.26.1
Pytorch 1.13.1+cu116
Datasets 2.10.1
Tokenizers 0.13.2
