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xlm-roberta-large-qqp-10 – AI Model by tmnam20 | AlphaNeural AI
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tmnam20
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xlm-roberta-large-qqp-10
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transformers
safetensors
xlm-roberta
text-classification
generated_from_trainer
en
tmnam20/VieGLUE
FacebookAI/xlm-roberta-large
finetune
mit
model-index
autotrain_compatible
endpoints_compatible
us
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xlm-roberta-large-qqp-10
This model is a fine-tuned version of
xlm-roberta-large
on the tmnam20/VieGLUE/QQP dataset. It achieves the following results on the evaluation set:
Loss: 0.2671
Accuracy: 0.9010
F1: 0.8682
Combined Score: 0.8846
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: 32
eval_batch_size: 16
seed: 10
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3.0
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
Combined Score
0.2894
0.88
10000
0.2821
0.8794
0.8402
0.8598
0.2352
1.76
20000
0.2630
0.8931
0.8566
0.8748
0.1732
2.64
30000
0.2666
0.8995
0.8656
0.8826
Framework versions
Transformers 4.36.0
Pytorch 2.1.0+cu121
Datasets 2.15.0
Tokenizers 0.15.0
