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
• train_batch_size: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 20
• mixed_precision_training: Native AMP

Training results

Framework versions

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