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