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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