Edit model card
YAML Metadata Warning: empty or missing yaml metadata in repo card (https://huggingface.co/docs/hub/model-cards#model-card-metadata)

<<<<<<< HEAD

tags:

  • generated_from_trainer datasets:
  • financial_phrasebank model-index:
  • name: test_trainer_1 results: []

test_trainer_1

This model is a fine-tuned version of SALT-NLP/FLANG-Roberta on the financial_phrasebank dataset. It achieves the following results on the evaluation set:

  • eval_loss: 0.5963
  • eval_accuracy: 0.9242
  • eval_runtime: 4.3354
  • eval_samples_per_second: 97.337
  • eval_steps_per_second: 12.225
  • step: 0

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: 5e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 5

Framework versions

  • Transformers 4.24.0
  • Pytorch 1.12.1+cu113
  • Datasets 2.7.0
  • Tokenizers 0.13.2

    This is a demo model for our reference

    24191373ff05e3799b9c6f359e51b37b642f4865

Downloads last month
3
Hosted inference API
Text Classification
Examples
Examples
This model can be loaded on the Inference API on-demand.