drhyrum / bert-tiny-financial-news-sentiment

huggingface.co
Total runs: 22
24-hour runs: 1
7-day runs: 5
30-day runs: 3
Model's Last Updated: May 13 2025

Introduction of bert-tiny-financial-news-sentiment

Model Details of bert-tiny-financial-news-sentiment

finetuning-financial-news-sentiment

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

  • Loss: 0.3345
  • Accuracy: 0.8751
  • F1: 0.8751
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
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 2
Training results
Framework versions
  • Transformers 4.17.0
  • Pytorch 1.10.0+cu111
  • Datasets 2.0.0
  • Tokenizers 0.11.6

Runs of drhyrum bert-tiny-financial-news-sentiment on huggingface.co

22
Total runs
1
24-hour runs
0
3-day runs
5
7-day runs
3
30-day runs

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bert-tiny-financial-news-sentiment install

bert-tiny-financial-news-sentiment is an open source model from GitHub that offers a free installation service, and any user can find bert-tiny-financial-news-sentiment on GitHub to install. At the same time, huggingface.co provides the effect of bert-tiny-financial-news-sentiment install, users can directly use bert-tiny-financial-news-sentiment installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

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