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xlm-roberta-base-lowercase-high-accuracy – AI Model by tukhtashevshohruh | AlphaNeural AI
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xlm-roberta-base-lowercase-high-accuracy
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transformers
safetensors
xlm-roberta
token-classification
uz
FacebookAI/xlm-roberta-base
finetune
mit
autotrain_compatible
endpoints_compatible
us
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xlm-roberta-base-lowercase
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: 0.16673
Precision: 0.5710
Recall: 0.6137
F1: 0.5916
Training hyperparameters
The following hyperparameters were used during training:
learning_rate: 5e-05
train_batch_size: 2
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 8
optimizer: Use adamw_torch 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: 500
num_epochs: 3
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
0.1949
1.0
2206
0.1788
0.5315
0.5391
0.5353
0.1669
2.0
4412
0.1670
0.5353
0.5995
0.5656
0.1361
3.0
6618
0.1667
0.5710
0.6137
0.5916
Framework versions
Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0
