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xlm-roberta-checkpoints – AI Model by aryan2025 | AlphaNeural AI
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aryan2025
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xlm-roberta-checkpoints
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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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xlm-roberta-checkpoints
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: 0.6971
Accuracy: 0.6933
F1: 0.6915
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: 64
eval_batch_size: 64
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 256
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: 2
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
No log
1.0
152
0.7172
0.6785
0.6772
No log
2.0
304
0.6971
0.6933
0.6915
Framework versions
Transformers 4.57.0
Pytorch 2.8.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1
