deberta-v3-xsmall-beavertails-harmful-qa-classifier – AI Model by domenicrosati | AlphaNeural AI

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domenicrosati/
deberta-v3-xsmall-beavertails-harmful-qa-classifier

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text-classification

generated_from_trainer

microsoft/deberta-v3-xsmall

autotrain_compatible

endpoints_compatible

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deberta-v3-xsmall-beavertails-harmful-qa-classifier

This model is a fine-tuned version of microsoft/deberta-v3-xsmall on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.3043
Accuracy: 0.8716
Macro F1: 0.8716
Macro Precision: 0.8738
Macro Recall: 0.8736
Micro F1: 0.8716
Micro Precision: 0.8716
Micro Recall: 0.8716

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: 6e-06
train_batch_size: 128
eval_batch_size: 128
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 1000
num_epochs: 4
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Macro F1	Macro Precision	Macro Recall	Micro F1	Micro Precision	Micro Recall
0.3726	1.0	2349	0.3409	0.8573	0.8573	0.8581	0.8587	0.8573	0.8573	0.8573
0.3299	2.0	4698	0.3186	0.8669	0.8669	0.8697	0.8692	0.8669	0.8669	0.8669
0.3181	3.0	7047	0.3092	0.8683	0.8682	0.8715	0.8707	0.8683	0.8683	0.8683
0.3064	4.0	9396	0.3043	0.8716	0.8716	0.8738	0.8736	0.8716	0.8716	0.8716

Framework versions

Transformers 4.40.0
Pytorch 2.2.2+cu121
Datasets 2.19.0
Tokenizers 0.19.1