lgk03/WITHINAPPS_NDD-phoenix_test-tags

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WITHINAPPSNDD-phoenixtest-tags

This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

• —Loss: 0.0922
• —Accuracy: 0.9772
• —F1: 0.9772
• —Precision: 0.9781
• —Recall: 0.9772

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: 32
• —evalbatchsize: 32
• —seed: 42
• —gradientaccumulationsteps: 4
• —totaltrainbatch_size: 128
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —num_epochs: 2

Training results

Framework versions

• —Transformers 4.41.2
• —Pytorch 2.3.0+cu121
• —Datasets 2.19.2
• —Tokenizers 0.19.1