xlmr_bs8 – AI Model by ruizzisa | AlphaNeural AI

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ruizzisa/
xlmr_bs8

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token-classification

generated_from_trainer

FacebookAI/xlm-roberta-base

endpoints_compatible

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xlmr_bs8

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

Loss: 0.0319
Precision: 0.9651
Recall: 0.9676
F1: 0.9664
Accuracy: 0.9943

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_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 8

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.1533	1.0	389	0.0798	0.8693	0.9081	0.8883	0.9831
0.0805	2.0	778	0.0411	0.9236	0.9540	0.9386	0.9890
0.0434	3.0	1167	0.0246	0.9654	0.9579	0.9617	0.9939
0.0308	4.0	1556	0.0234	0.9735	0.9754	0.9745	0.9953
0.0252	5.0	1945	0.0211	0.9787	0.9832	0.9809	0.9960
0.0243	6.0	2334	0.0141	0.9851	0.9838	0.9845	0.9971
0.0211	7.0	2723	0.0152	0.9839	0.9871	0.9855	0.9970
0.0141	8.0	3112	0.0149	0.9858	0.9877	0.9867	0.9973

Framework versions

Transformers 5.13.1
Pytorch 2.11.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2