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hing_xlmr – AI Model by amaan00z | AlphaNeural AI
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hing_xlmr
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transformers
tensorboard
safetensors
xlm-roberta
text-classification
generated_from_trainer
FacebookAI/xlm-roberta-base
finetune
mit
text-embeddings-inference
endpoints_compatible
us
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hing_xlmr
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: 0.0339
Accuracy: 0.993
F1 Macro: 0.9930
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: 32
eval_batch_size: 32
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: 4
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1 Macro
0.7382
1.0
844
0.0516
0.9877
0.9878
0.0395
2.0
1688
0.0562
0.99
0.9901
0.0261
3.0
2532
0.0284
0.994
0.9940
0.0128
4.0
3376
0.0339
0.993
0.9930
Framework versions
Transformers 4.57.1
Pytorch 2.8.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1
