asadfgglie/mDeBERTa-v3-base-xnli-multilingual-zeroshot-v4.0-only-nli-downsample

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mDeBERTa-v3-base-xnli-multilingual-zeroshot-v4.0-only-nli-downsample

This model use same dataset with asadfgglie/mDeBERTa-v3-base-xnli-multilingual-zeroshot-v1.0, but training set was downsampled as 80% size of non-nli dataset asadfgglie/BanBan_2024-10-17-facial_expressions-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: 0.4486
• —F1 Macro: 0.8264
• —F1 Micro: 0.8274
• —Accuracy Balanced: 0.8270
• —Accuracy: 0.8274
• —Precision Macro: 0.8260
• —Recall Macro: 0.8270
• —Precision Micro: 0.8274
• —Recall Micro: 0.8274

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
• —trainbatchsize: 16
• —evalbatchsize: 128
• —seed: 20241201
• —gradientaccumulationsteps: 2
• —totaltrainbatch_size: 32
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —lrschedulerwarmup_ratio: 0.06
• —num_epochs: 3

Training results

Eval results

Framework versions

• —Transformers 4.33.3
• —Pytorch 2.5.1+cu121
• —Datasets 2.14.7
• —Tokenizers 0.13.3