DynamicNoise-deberta-v3-small-Label_A

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

• Loss: 0.0012
• Accuracy: 0.9999
• F1: 0.9999
• Precision: 0.9999
• Recall: 0.9999

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: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 32
• optimizer: Use 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_steps: 500
• num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.0	0.9997	1599	0.0012	0.9999	0.9999	0.9999	0.9999

Framework versions

• Transformers 4.47.0
• Pytorch 2.5.1+cu124
• Datasets 2.18.0
• Tokenizers 0.21.0