peaceful-newt-854 – AI Model by ElMad | AlphaNeural AI

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ElMad/
peaceful-newt-854

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text-classification

generated_from_trainer

microsoft/deberta-v3-base

autotrain_compatible

endpoints_compatible

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peaceful-newt-854

This model is a fine-tuned version of microsoft/deberta-v3-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.3128
Hamming Loss: 0.1103
Zero One Loss: 0.9812
Jaccard Score: 0.9806
Hamming Loss Optimised: 0.0956
Hamming Loss Threshold: 0.4050
Zero One Loss Optimised: 0.7863
Zero One Loss Threshold: 0.2848
Jaccard Score Optimised: 0.7837
Jaccard Score Threshold: 0.2860

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: 4.5932967632023205e-06
train_batch_size: 32
eval_batch_size: 32
seed: 2024
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Hamming Loss	Zero One Loss	Jaccard Score	Hamming Loss Optimised	Hamming Loss Threshold	Zero One Loss Optimised	Zero One Loss Threshold	Jaccard Score Optimised	Jaccard Score Threshold
No log	1.0	100	0.3818	0.1123	1.0	1.0	0.1123	0.5944	0.7662	0.3477	0.7638	0.3334
No log	2.0	200	0.3372	0.1123	1.0	1.0	0.1123	0.9000	1.0	0.9000	1.0	0.9000
No log	3.0	300	0.3192	0.1123	1.0	1.0	0.0969	0.3709	0.7150	0.1960	0.6977	0.1844
No log	4.0	400	0.3128	0.1103	0.9812	0.9806	0.0956	0.4050	0.7863	0.2848	0.7837	0.2860

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu124
Datasets 3.1.0
Tokenizers 0.21.0