relex_pre – AI Model by KKrueger | AlphaNeural AI

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KKrueger/
relex_pre

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text-classification

generated_from_trainer

FacebookAI/xlm-roberta-large

autotrain_compatible

endpoints_compatible

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relex_pre

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

Loss: 0.4173
Macro F1: 0.9040

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: 1e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Use 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: 7

Training results

Training Loss	Epoch	Step	Validation Loss	Macro F1
0.8776	1.0	1328	0.3809	0.7517
0.2962	2.0	2656	0.3053	0.8606
0.2057	3.0	3984	0.3026	0.8932
0.1408	4.0	5312	0.3286	0.9079
0.0961	5.0	6640	0.4013	0.8945
0.0628	6.0	7968	0.4145	0.9037
0.042	7.0	9296	0.4173	0.9040

Framework versions

Transformers 4.51.3
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1