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dsc25-nextlevelv2-mdeberta-xnli-v1 – AI Model by htNghiaaa | AlphaNeural AI
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htNghiaaa
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dsc25-nextlevelv2-mdeberta-xnli-v1
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transformers
safetensors
deberta-v2
text-classification
generated_from_trainer
MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7
finetune
mit
text-embeddings-inference
endpoints_compatible
us
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mdeberta-xnli-v1
This model is a fine-tuned version of
MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7
on the None dataset. It achieves the following results on the evaluation set:
Loss: 1.2558
F1 Macro: 0.6647
F1 Weighted: 0.6643
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: 3e-05
train_batch_size: 4
eval_batch_size: 8
seed: 42
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
lr_scheduler_warmup_ratio: 0.1
num_epochs: 5
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
F1 Macro
F1 Weighted
0.8134
1.0
1620
0.8680
0.6311
0.6299
0.696
2.0
3240
1.0074
0.6678
0.6673
0.6486
3.0
4860
1.0948
0.6525
0.6525
0.5952
4.0
6480
1.2558
0.6647
0.6643
Framework versions
Transformers 4.56.2
Pytorch 2.8.0+cu128
Datasets 4.1.1
Tokenizers 0.22.1
