rogue-crane-540 – AI Model by ElMad | AlphaNeural AI

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ElMad/
rogue-crane-540

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google-bert/bert-base-cased

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rogue-crane-540

This model is a fine-tuned version of google-bert/bert-base-cased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.6200
Hamming Loss: 0.2812
Zero One Loss: 1.0
Jaccard Score: 0.8617
Hamming Loss Optimised: 0.1123
Hamming Loss Threshold: 0.6724
Zero One Loss Optimised: 0.8575
Zero One Loss Threshold: 0.5775
Jaccard Score Optimised: 0.8790
Jaccard Score Threshold: 0.3808

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: 2.4790601469455396e-05
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: 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	100	0.6447	0.36	1.0	0.8848	0.1123	0.6863	0.915	0.5569	0.8878	0.2889
No log	2.0	200	0.6200	0.2812	1.0	0.8617	0.1123	0.6724	0.8575	0.5775	0.8790	0.3808

Framework versions

PEFT 0.13.2
Transformers 4.47.0
Pytorch 2.5.1+cu124
Datasets 3.1.0
Tokenizers 0.21.0