melodic-bee-938 – AI Model by ElMad | AlphaNeural AI

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ElMad/
melodic-bee-938

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text-classification

generated_from_trainer

FacebookAI/roberta-base

autotrain_compatible

endpoints_compatible

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melodic-bee-938

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: 0.3387
Hamming Loss: 0.1123
Zero One Loss: 1.0
Jaccard Score: 1.0
Hamming Loss Optimised: 0.1123
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: 0.0011128424281972827
train_batch_size: 32
eval_batch_size: 32
seed: 2024
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 9

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
0.3511	1.0	100	0.3435	0.1123	1.0	1.0	0.1123	0.9000	1.0	0.9000	1.0	0.9000
0.3408	2.0	200	0.3418	0.1123	1.0	1.0	0.1123	0.9000	1.0	0.9000	1.0	0.9000
0.3393	3.0	300	0.3440	0.1123	1.0	1.0	0.1123	0.9000	1.0	0.9000	1.0	0.9000
0.3377	4.0	400	0.3395	0.1123	1.0	1.0	0.1123	0.9000	1.0	0.9000	1.0	0.9000
0.3363	5.0	500	0.3408	0.1123	1.0	1.0	0.1123	0.9000	1.0	0.9000	1.0	0.9000
0.3362	6.0	600	0.3397	0.1123	1.0	1.0	0.1123	0.9000	1.0	0.9000	1.0	0.9000
0.3349	7.0	700	0.3420	0.1123	1.0	1.0	0.1123	0.9000	1.0	0.9000	1.0	0.9000
0.334	8.0	800	0.3397	0.1123	1.0	1.0	0.1123	0.9000	1.0	0.9000	1.0	0.9000
0.3337	9.0	900	0.3387	0.1123	1.0	1.0	0.1123	0.9000	1.0	0.9000	1.0	0.9000

Framework versions

Transformers 4.45.1
Pytorch 2.5.1+cu124
Datasets 3.1.0
Tokenizers 0.20.3