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Llama-Prompt-Guard-2-22M-ft-custom – AI Model by alilf | AlphaNeural AI
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Llama-Prompt-Guard-2-22M-ft-custom
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transformers
safetensors
bert
text-classification
generated_from_trainer
HooshvareLab/bert-base-parsbert-uncased
finetune
text-embeddings-inference
endpoints_compatible
us
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Llama-Prompt-Guard-2-22M-ft-custom
This model is a fine-tuned version of
HooshvareLab/bert-base-parsbert-uncased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.1352
Accuracy: 1.0
Precision: 1.0000
Recall: 1.0000
F1: 1.0000
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: 64
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: 3.0
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
Precision
Recall
F1
No log
1.0
8
0.3232
0.9667
0.9500
1.0000
0.9744
No log
2.0
16
0.1534
1.0
1.0000
1.0000
1.0000
No log
3.0
24
0.1194
1.0
1.0000
1.0000
1.0000
Framework versions
Transformers 4.53.3
Pytorch 2.6.0+cu124
Datasets 4.4.1
Tokenizers 0.21.2
