xlmr_positive_negative – AI Model by Naren-Kandasamy | AlphaNeural AI

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Naren-Kandasamy/
xlmr_positive_negative

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text-classification

generated_from_trainer

FacebookAI/xlm-roberta-base

text-embeddings-inference

endpoints_compatible

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xlmr_positive_negative

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

Loss: 0.6680
Accuracy: 0.6667
F1: 0.6581

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: 16
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: 6
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
No log	1.0	57	0.6944	0.5570	0.5525
No log	2.0	114	0.6491	0.6623	0.6324
No log	3.0	171	0.6193	0.6842	0.6708
No log	4.0	228	0.6263	0.7018	0.6796
No log	5.0	285	0.6412	0.6535	0.6478
No log	6.0	342	0.6680	0.6667	0.6581

Framework versions

Transformers 5.1.0
Pytorch 2.9.0+cu126
Datasets 4.5.0
Tokenizers 0.22.2