lct-rug-2022/edos-2023-baseline-bert-base-multilingual-uncased-label_vector

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edos-2023-baseline-bert-base-multilingual-uncased-label_vector

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

• —Loss: 1.6113
• —F1: 0.2785

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: 1e-05
• —trainbatchsize: 32
• —evalbatchsize: 32
• —seed: 42
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —lrschedulerwarmup_steps: 5
• —num_epochs: 12
• —mixedprecisiontraining: Native AMP

Training results

Framework versions

• —Transformers 4.24.0
• —Pytorch 1.12.1+cu113
• —Datasets 2.7.1
• —Tokenizers 0.13.2