BEE-spoke-data / roberta-large-title2genre

huggingface.co
Total runs: 13
24-hour runs: 0
7-day runs: 1
30-day runs: 5
Model's Last Updated: December 29 2025
text-classification

Introduction of roberta-large-title2genre

Model Details of roberta-large-title2genre


roberta-large-mnli for title-genre classification

This model is a fine-tuned version of roberta-large-mnli on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2758
  • F1: 0.5464
Model description

This classifies one or more genre labels in a multi-label setting for a given book title .

The 'standard' way of interpreting the predictions is that the predicted labels for a given example are only the ones with a greater than 50% probability.

Training procedure
Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 6e-05
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-10
  • lr_scheduler_type: linear
  • num_epochs: 5.0
Training results
Training Loss Epoch Step Validation Loss F1
0.3096 1.0 62 0.2862 0.3707
0.2863 2.0 124 0.2804 0.4422
0.2618 3.0 186 0.2773 0.4989
0.2432 4.0 248 0.2764 0.5223
0.2241 5.0 310 0.2758 0.5464
Framework versions
  • Transformers 4.33.3
  • Pytorch 2.2.0.dev20231001+cu121
  • Datasets 2.14.5
  • Tokenizers 0.13.3

Runs of BEE-spoke-data roberta-large-title2genre on huggingface.co

13
Total runs
0
24-hour runs
0
3-day runs
1
7-day runs
5
30-day runs

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roberta-large-title2genre install

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