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deberta-v3-xsmall-finetuned-content-moderator – AI Model by mothy-08 | AlphaNeural AI
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mothy-08
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deberta-v3-xsmall-finetuned-content-moderator
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transformers
safetensors
deberta-v2
text-classification
generated_from_trainer
en
google/civil_comments
ucberkeley-dlab/measuring-hate-speech
microsoft/deberta-v3-xsmall
finetune
mit
text-embeddings-inference
endpoints_compatible
us
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deberta-v3-xsmall-finetuned-content-moderator
This model is a fine-tuned version of
microsoft/deberta-v3-xsmall
on the
google/civil_comments
and
ucberkeley-dlab/measuring-hate-speech
dataset.
It achieves the following results on the evaluation set:
Loss: 0.2450
Accuracy: 0.9086
F1: 0.9124
Precision: 0.8757
Recall: 0.9523
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: 32
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
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
Precision
Recall
0.2528
1.0
7650
0.2359
0.9044
0.9084
0.8718
0.9482
0.2161
2.0
15300
0.2423
0.9060
0.9105
0.8690
0.9563
0.1988
3.0
22950
0.2450
0.9086
0.9124
0.8757
0.9523
Framework versions
Transformers 4.57.1
Pytorch 2.9.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1
