urgency_classifier – AI Model by sambodhan | AlphaNeural AI

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sambodhan/
urgency_classifier

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text-classification

generated_from_trainer

FacebookAI/xlm-roberta-base

text-embeddings-inference

endpoints_compatible

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urgency_classifier

This model is a fine-tuned version of xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.0258
Accuracy: 0.9187
F1 Macro: 0.9201
F1 Weighted: 0.9185
Precision Macro: 0.9203
Recall Macro: 0.9221
Precision Weighted: 0.9204
Recall Weighted: 0.9187

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: 16
eval_batch_size: 32
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
num_epochs: 3
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1 Macro	F1 Weighted	Precision Macro	Recall Macro	Precision Weighted	Recall Weighted
0.0969	0.625	50	0.0419	0.7625	0.7566	0.7447	0.7724	0.7877	0.7773	0.7625
0.031	1.25	100	0.0272	0.8688	0.8704	0.8658	0.8697	0.8804	0.8725	0.8688
0.0202	1.875	150	0.0232	0.9	0.9022	0.8993	0.9015	0.9060	0.9015	0.9
0.0132	2.5	200	0.0258	0.9187	0.9201	0.9185	0.9203	0.9221	0.9204	0.9187

Framework versions

Transformers 4.57.1
Pytorch 2.9.0+cu128
Datasets 4.3.0
Tokenizers 0.22.1