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Bert-Contact-NLI – AI Model by osmanh | AlphaNeural AI
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osmanh
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Bert-Contact-NLI
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transformers
safetensors
deberta-v2
text-classification
generated_from_trainer
zero-shot-classification
kiddothe2b/contract-nli
MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7
finetune
mit
autotrain_compatible
endpoints_compatible
us
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Bert-Contact-NLI
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: 0.9601
Model Preparation Time: 0.0101
Accuracy: 0.6358
Precision: 0.6154
Recall: 0.6254
F1: 0.6161
Ratio: 0.4969
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: 8
eval_batch_size: 8
seed: 42
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
num_epochs: 1
Training results
Training Loss
Epoch
Step
Validation Loss
Model Preparation Time
Accuracy
Precision
Recall
F1
Ratio
No log
1.0
95
0.9601
0.0101
0.6358
0.6154
0.6254
0.6161
0.4969
Framework versions
Transformers 4.46.2
Pytorch 2.5.1+cu121
Datasets 3.1.0
Tokenizers 0.20.3
