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glot500_Inj_ru_taiga – AI Model by ibrahimbukhari1998 | AlphaNeural AI
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glot500_Inj_ru_taiga
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transformers
safetensors
xlm-roberta
token-classification
generated_from_trainer
FacebookAI/xlm-roberta-base
finetune
mit
autotrain_compatible
endpoints_compatible
us
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glot500_Inj_ru_taiga
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: 0.2234
Precision: 0.9239
Recall: 0.9271
F1: 0.9255
Accuracy: 0.9410
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
No log
1.0
197
0.2973
0.9009
0.9044
0.9026
0.9246
No log
2.0
394
0.2234
0.9239
0.9271
0.9255
0.9410
Framework versions
Transformers 4.46.3
Pytorch 2.5.1
Datasets 3.1.0
Tokenizers 0.20.3
