valurank/distilroberta-topic-classification

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distilroberta-topic-classification

This model is a fine-tuned version of distilroberta-topic-base on a dataset of headlines. It achieves the following results on the evaluation set:

• —Loss: 2.235735
• —F1: 0.756

Training and evaluation data

The following data sources were used:

• —22k News articles classified into 120 different topics from Hugging face

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• —learning_rate: 5e-05
• —trainbatchsize: 32
• —evalbatchsize: 32
• —seed: 12345
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —lrschedulerwarmup_steps: 16
• —num_epochs: 10
• —mixedprecisiontraining: Native AMP

Training results

Framework versions

• —Transformers 4.35.2
• —Pytorch 2.1.0
• —Datasets 2.15.0
• —Tokenizers 0.15.0