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results – AI Model by Neperl | AlphaNeural AI
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transformers
safetensors
xlm-roberta
text-classification
generated_from_trainer
FacebookAI/xlm-roberta-base
finetune
mit
endpoints_compatible
us
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This model is a fine-tuned version of
xlm-roberta-base
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.6172
Accuracy: 0.76
F1: 0.7072
Precision: 0.7083
Recall: 0.7067
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: 5e-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_steps: 100
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
Precision
Recall
0.6343
1.0
1000
0.6225
0.734
0.6645
0.6735
0.6667
0.5747
2.0
2000
0.6149
0.757
0.7002
0.7042
0.6992
0.4936
3.0
3000
0.6172
0.76
0.7072
0.7083
0.7067
Framework versions
Transformers 5.12.1
Pytorch 2.11.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2
