jamesbaskerville/classify-articles

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classify-articles

This model is a fine-tuned version of albert/albert-base-v2 on the None dataset. It achieves the following results on the evaluation set:

• —Loss: 0.3819
• —Accuracy: 0.9070
• —F1: 0.9061
• —Precision: 0.9126
• —Recall: 0.9070
• —Accuracy Label Economy: 0.9429
• —Accuracy Label Politics: 0.9574
• —Accuracy Label Science: 0.9362
• —Accuracy Label Sports: 0.96
• —Accuracy Label Technology: 0.6944

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: 16
• —evalbatchsize: 16
• —seed: 42
• —gradientaccumulationsteps: 2
• —totaltrainbatch_size: 32
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —lrschedulerwarmup_steps: 500
• —num_epochs: 3

Training results

Framework versions

• —Transformers 4.44.2
• —Pytorch 2.4.1
• —Datasets 2.21.0
• —Tokenizers 0.19.1