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pwnb-rmfc – AI Model by rollingkevin | AlphaNeural AI
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rollingkevin
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pwnb-rmfc
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transformers
pytorch
tensorboard
roberta
text-classification
generated_from_trainer
mit
autotrain_compatible
endpoints_compatible
us
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Model card
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roberta-mnli-finetune-config
This model is a fine-tuned version of
roberta-large-mnli
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.6113
Accuracy: 0.8673
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: 4
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.5638
1.0
10108
0.5104
0.8584
0.4304
2.0
20216
0.6113
0.8673
Framework versions
Transformers 4.16.2
Pytorch 1.10.0+cu111
Datasets 1.18.3
Tokenizers 0.11.0
