gregarious-stork-277 – AI Model by ElMad | AlphaNeural AI

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ElMad/
gregarious-stork-277

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text-classification

generated_from_trainer

FacebookAI/roberta-base

autotrain_compatible

endpoints_compatible

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gregarious-stork-277

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

Loss: 0.1653
Hamming Loss: 0.0585
Zero One Loss: 0.37
Jaccard Score: 0.3184
Hamming Loss Optimised: 0.0573
Hamming Loss Threshold: 0.6528
Zero One Loss Optimised: 0.3638
Zero One Loss Threshold: 0.4756
Jaccard Score Optimised: 0.3036
Jaccard Score Threshold: 0.3778

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: 4.699473391301759e-05
train_batch_size: 4
eval_batch_size: 4
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: 3

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
0.2588	1.0	800	0.1743	0.0609	0.4875	0.4465	0.0615	0.5889	0.4087	0.3632	0.3315	0.2248
0.1588	2.0	1600	0.1652	0.0589	0.4187	0.3728	0.0585	0.7092	0.3912	0.4568	0.3239	0.2272
0.1293	3.0	2400	0.1653	0.0585	0.37	0.3184	0.0573	0.6528	0.3638	0.4756	0.3036	0.3778

Framework versions

Transformers 4.47.0
Pytorch 2.5.1+cu124
Datasets 3.1.0
Tokenizers 0.21.0