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roberta-base-category-classifier – AI Model by chunwei-sf | AlphaNeural AI
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chunwei-sf
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roberta-base-category-classifier
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peft
safetensors
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lora
transformers
FacebookAI/roberta-base
adapter
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roberta-base-category-classifier
This model is a fine-tuned version of
roberta-base
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.1074
Accuracy: 0.9717
Precision: 0.9715
Recall: 0.9717
F1: 0.9715
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: 16
eval_batch_size: 16
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
Precision
Recall
F1
0.2522
1.0
1342
0.1409
0.9594
0.9592
0.9594
0.9589
0.1339
2.0
2684
0.1094
0.9709
0.9707
0.9709
0.9707
0.1098
3.0
4026
0.1074
0.9717
0.9715
0.9717
0.9715
Framework versions
PEFT 0.17.1
Transformers 4.55.4
Pytorch 2.8.0+cu126
Datasets 4.0.0
Tokenizers 0.21.4
