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curse_classification – AI Model by djsull | AlphaNeural AI
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curse_classification
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curse_classification
This model is a fine-tuned version of
klue/roberta-small
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.2780
Precision: 0.8727
Recall: 0.8752
F1: 0.8739
Accuracy: 0.8835
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: 5e-05
train_batch_size: 128
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
0.3511
1.0
618
0.2939
0.8532
0.8591
0.8561
0.8720
0.2546
2.0
1236
0.2924
0.8721
0.8552
0.8636
0.8802
Framework versions
Transformers 4.42.3
Pytorch 2.3.0+cu121
Datasets 2.18.0
Tokenizers 0.19.1
