kugler/gbert-large-AmDi.tiny-synset-classifier

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gbertsynsetclassifieramditiny

This model is a fine-tuned version of deepset/gbert-large on an unknown dataset. It achieves the following results on the evaluation set:

• —Loss: 0.6469
• —Accuracy: 0.8376
• —F1: 0.8366
• —Precision: 0.8446
• —Recall: 0.8376
• —F1 Macro: 0.8202
• —Precision Macro: 0.7900
• —Recall Macro: 0.8625
• —F1 Micro: 0.8376
• —Precision Micro: 0.8376
• —Recall Micro: 0.8376

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
• —lrschedulerwarmup_steps: 50
• —num_epochs: 10
• —mixedprecisiontraining: Native AMP

Training results

Framework versions

• —Transformers 4.45.2
• —Pytorch 2.3.1+cu121
• —Datasets 2.20.0
• —Tokenizers 0.20.3