bustling-sheep-989 – AI Model by ElMad | AlphaNeural AI

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ElMad/
bustling-sheep-989

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microsoft/deberta-v3-small

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bustling-sheep-989

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

Loss: 0.7152
Hamming Loss: 0.4695
Zero One Loss: 1.0
Jaccard Score: 0.8591
Hamming Loss Optimised: 0.1123
Hamming Loss Threshold: 0.6789
Zero One Loss Optimised: 0.8662
Zero One Loss Threshold: 0.5944
Jaccard Score Optimised: 0.8445
Jaccard Score Threshold: 0.5669

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: 3.2020206916802435e-06
train_batch_size: 8
eval_batch_size: 8
seed: 2024
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.8180574670796091,0.9816119412827323) and epsilon=1e-07 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	400	0.7155	0.4695	1.0	0.8591	0.1123	0.6789	0.8662	0.5944	0.8445	0.5669
0.717	2.0	800	0.7152	0.4695	1.0	0.8591	0.1123	0.6789	0.8662	0.5944	0.8445	0.5669

Framework versions

PEFT 0.13.2
Transformers 4.48.0.dev0
Pytorch 2.5.1+cu124
Datasets 3.1.0
Tokenizers 0.21.0