restar_v1.0_model – AI Model by Aurelianous | AlphaNeural AI

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Aurelianous/
restar_v1.0_model

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text-classification

generated_from_trainer

text-embeddings-inference

endpoints_compatible

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restar_v1.0_model

This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.5218
Accuracy: 0.8348
F1 Macro: 0.6848
Confusion Matrix: [[82465, 26863, 3426], [18567, 49076, 11286], [15442, 82987, 669888]]

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: 3e-05
train_batch_size: 64
eval_batch_size: 64
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.06
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1 Macro	Confusion Matrix
0.2499	1.0	4688	0.6122	0.8257	0.6741	[[24622, 12042, 1110], [4536, 17557, 3968], [4031, 30080, 222054]]
0.3252	2.0	9376	0.5233	0.8339	0.6838	[[27696, 8969, 1109], [6104, 16171, 3786], [5149, 28027, 222989]]
0.2379	3.0	14064	0.6115	0.8312	0.6797	[[27286, 9322, 1166], [5976, 16152, 3933], [5360, 28268, 222537]]

Framework versions

Transformers 4.57.1
Pytorch 2.9.0+cu126
Datasets 3.6.0
Tokenizers 0.22.2