sentiment-XLM-RoBERTa-es-2025_II-bs16 – AI Model by Elkin5 | AlphaNeural AI

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Elkin5/
sentiment-XLM-RoBERTa-es-2025_II-bs16

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text-classification

generated_from_trainer

FacebookAI/xlm-roberta-large

text-embeddings-inference

endpoints_compatible

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sentiment-XLM-RoBERTa-es-2025_II-bs16

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

Loss: 1.0996
F1 Macro: 0.1868
F1 Weighted: 0.2182
Accuracy: 0.3893

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
lr_scheduler_warmup_ratio: 0.1
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	F1 Macro	F1 Weighted	Accuracy
1.0985	1.0	241	1.0994	0.1878	0.2211	0.3923
1.1068	2.0	482	1.0987	0.1878	0.2211	0.3923
1.1062	3.0	723	1.0989	0.1606	0.1529	0.3174
1.1059	4.0	964	1.0988	0.15	0.1306	0.2903

Framework versions

Transformers 4.57.1
Pytorch 2.8.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1