sentiment-xlm-roberta – AI Model by hassen228 | AlphaNeural AI

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hassen228/
sentiment-xlm-roberta

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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

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: 1.0890
Accuracy: 0.3979
Precision: 0.1326
Recall: 0.3333
F1: 0.1898

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: 4
eval_batch_size: 4
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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
1.1048	1.0	1141	1.1043	0.3819	0.1273	0.3333	0.1842
1.1082	2.0	2282	1.0943	0.3819	0.1273	0.3333	0.1842
1.1037	3.0	3423	1.0956	0.3819	0.1273	0.3333	0.1842
1.1019	4.0	4564	1.0940	0.3819	0.1273	0.3333	0.1842
1.1024	5.0	5705	1.0945	0.3819	0.1273	0.3333	0.1842
1.0966	6.0	6846	1.0933	0.3819	0.1273	0.3333	0.1842
1.0994	7.0	7987	1.0950	0.3819	0.1273	0.3333	0.1842
1.0962	8.0	9128	1.0961	0.3819	0.1273	0.3333	0.1842

Framework versions

Transformers 4.57.1
Pytorch 2.8.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1