marieke93/BERT-evidence-types

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BERT-evidence-types

This model is a fine-tuned version of bert-base-uncased on the evidence types dataset. It achieves the following results on the evaluation set:

• —Loss: 2.8008
• —Macro f1: 0.4227
• —Weighted f1: 0.6976
• —Accuracy: 0.7154
• —Balanced accuracy: 0.3876

Training and evaluation data

The data set, as well as the code that was used to fine tune this model can be found in the GitHub repository BA-Thesis-Information-Science-Persuasion-Strategies

Training hyperparameters

The following hyperparameters were used during training:

• —learning_rate: 3e-05
• —trainbatchsize: 32
• —evalbatchsize: 32
• —seed: 42
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —num_epochs: 20
• —mixedprecisiontraining: Native AMP

Training results

Framework versions

• —Transformers 4.19.2
• —Pytorch 1.11.0+cu113
• —Datasets 2.2.2
• —Tokenizers 0.12.1