MiniLM-evidence-types

This model is a fine-tuned version of microsoft/MiniLM-L12-H384-uncased on the evidence types dataset. It achieved the following results on the evaluation set:

• Loss: 1.8672
• Macro f1: 0.3726
• Weighted f1: 0.7030
• Accuracy: 0.7161
• Balanced accuracy: 0.3616

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: 2e-05
• train_batch_size: 16
• eval_batch_size: 16
• 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