samchain/EconoDetect-US

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EconoDetect

This model is a fine-tuned version of samchain/econo-sentence-v2 on the economics-relevance dataset. The base model is kept frozen during training, only the classification head is updated.

It achieves the following results on the evaluation set:

• —Loss: 0.3973
• —Accuracy: 0.8211
• —F1: 0.7991
• —Precision: 0.7895
• —Recall: 0.8211

Model description

This model is designed to detect whether a text discusses topics related to the US economy.

Intended uses & limitations

The model can be used as a screening tool to remove texts that are not discussing US economy.

Training and evaluation data

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• —learning_rate: 0.0005
• —trainbatchsize: 8
• —evalbatchsize: 16
• —seed: 42
• —optimizer: Use adamwtorch with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
• —lrschedulertype: linear
• —lrschedulerwarmup_steps: 100
• —num_epochs: 3

Training results

Framework versions

• —Transformers 4.50.0
• —Pytorch 2.1.0+cu118
• —Datasets 3.4.1
• —Tokenizers 0.21.1