XLMR-Cross-Lingual-NER – AI Model by Sharpaxis | AlphaNeural AI

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Sharpaxis/
XLMR-Cross-Lingual-NER

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token-classification

generated_from_trainer

FacebookAI/xlm-roberta-base

autotrain_compatible

endpoints_compatible

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XLMR-Cross-Lingual-NER

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: 0.1420
F1: 0.8621

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 2e-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: 3

Training results

Training Loss	Epoch	Step	Validation Loss	F1
0.2896	1.0	787	0.1600	0.8287
0.1374	2.0	1574	0.1421	0.8560
0.1017	3.0	2361	0.1420	0.8621

Framework versions

Transformers 4.46.3
Pytorch 2.4.0
Datasets 3.1.0
Tokenizers 0.20.3