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XLMR-multi-en-wo – AI Model by summerdevlin46 | AlphaNeural AI
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XLMR-multi-en-wo
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transformers
tensorboard
safetensors
xlm-roberta
token-classification
generated_from_trainer
FacebookAI/xlm-roberta-base
finetune
mit
autotrain_compatible
endpoints_compatible
us
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XLMR-multi-en-wo
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: 0.1789
Precision: 0.9177
Recall: 0.9293
F1: 0.9235
Accuracy: 0.9348
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 with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 2
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
0.554
1.0
700
0.2201
0.8948
0.9106
0.9026
0.9162
0.1935
2.0
1400
0.1789
0.9177
0.9293
0.9235
0.9348
Framework versions
Transformers 4.48.3
Pytorch 2.5.1+cu124
Datasets 3.3.1
Tokenizers 0.21.0
