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LLMGUARD-roberta-11 – AI Model by Hemg | AlphaNeural AI
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Hemg
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LLMGUARD-roberta-11
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transformers
safetensors
roberta
text-classification
generated_from_trainer
FacebookAI/roberta-base
finetune
mit
autotrain_compatible
endpoints_compatible
us
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LLMGUARD-roberta-11
This model is a fine-tuned version of
FacebookAI/roberta-base
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.6189
Accuracy: 0.7964
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: 3e-06
train_batch_size: 16
eval_batch_size: 8
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 4
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.7894
1.0
1585
0.6954
0.7818
0.6249
2.0
3170
0.6336
0.7936
0.5562
3.0
4755
0.6232
0.7953
0.5416
4.0
6340
0.6189
0.7964
Framework versions
Transformers 4.48.0.dev0
Pytorch 2.5.1+cu124
Datasets 3.2.0
Tokenizers 0.21.0
