sincere-bat-931 – AI Model by ElMad | AlphaNeural AI

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ElMad/
sincere-bat-931

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text-classification

generated_from_trainer

microsoft/deberta-v3-xsmall

autotrain_compatible

endpoints_compatible

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sincere-bat-931

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

Loss: 0.1825
Hamming Loss: 0.0494
Zero One Loss: 1.0
Jaccard Score: 1.0
Hamming Loss Optimised: 0.0494
Hamming Loss Threshold: 0.9000
Zero One Loss Optimised: 1.0
Zero One Loss Threshold: 0.9000
Jaccard Score Optimised: 1.0
Jaccard Score Threshold: 0.9000

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: 5.0943791435964314e-05
train_batch_size: 20
eval_batch_size: 20
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: 2

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	160	0.1862	0.0497	1.0	1.0	0.0497	0.9000	1.0	0.9000	1.0	0.9000
No log	2.0	320	0.1838	0.0497	1.0	1.0	0.0497	0.9000	1.0	0.9000	1.0	0.9000

Framework versions

Transformers 4.46.3
Pytorch 2.5.1+cu118
Datasets 3.1.0
Tokenizers 0.20.3