nli-professional-status – AI Model by selsar | AlphaNeural AI

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selsar/
nli-professional-status

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text-classification

generated_from_trainer

EuroBERT/EuroBERT-610m

autotrain_compatible

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nli-professional-status

This model is a fine-tuned version of EuroBERT/EuroBERT-610m on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.5105
Accuracy: 0.8906
Precision Binary: 0.5169
Recall Binary: 0.3770
F1 Binary: 0.4360
Precision Micro: 0.8906
Recall Micro: 0.8906
F1 Micro: 0.8906
F1 Macro: 0.6877
Pr Auc: 0.8671
Cohen Kappa: 0.3771

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: 2e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
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	Accuracy	Precision Binary	Recall Binary	F1 Binary	Precision Micro	Recall Micro	F1 Micro	F1 Macro	Pr Auc	Cohen Kappa
0.4706	1.0	544	0.3099	0.8925	0.5472	0.2377	0.3314	0.8925	0.8925	0.8925	0.6365	0.8528	0.2827
0.3256	2.0	1088	0.4521	0.8998	0.6275	0.2623	0.3699	0.8998	0.8998	0.8998	0.6578	0.8660	0.3253
0.2073	3.0	1632	0.5105	0.8906	0.5169	0.3770	0.4360	0.8906	0.8906	0.8906	0.6877	0.8671	0.3771

Framework versions

Transformers 4.52.2
Pytorch 2.6.0+cu124
Datasets 2.14.4
Tokenizers 0.21.1