README.md

metadata

license: cc
language:
  - tr
metrics:
  - accuracy
  - precision
  - recall
  - f1
library_name: bertopic
pipeline_tag: text-classification
tags:
  - finance

Model Description

• Developed by: Mikail Doğruer
• Model type: 128k Bert Model
• Language(s) (NLP): Turkish

{'eval_loss': 0.25295722484588623, 'eval_accuracy': 0.9484536082474226, 'eval_precision': 0.9497797985940278, 'eval_recall': 0.9463618552943321, 'eval_f1': 0.9479608415152083, 'eval_runtime': 1.5618, 'eval_samples_per_second': 186.318, 'eval_steps_per_second': 1.921, 'epoch': 12.0}

Epoch Training Loss Validation Loss Accuracy Precision Recall F1

• 1 0.297100 0.253670 0.945017 0.945524 0.942778 0.944051

• 2 0.279300 0.253695 0.945017 0.945524 0.942778 0.944051

• 3 0.278800 0.253687 0.945017 0.945524 0.942778 0.944051

• 4 0.299700 0.253546 0.948454 0.949780 0.946362 0.947961

• 5 0.293400 0.253468 0.948454 0.949780 0.946362 0.947961

• 6 0.316400 0.253449 0.948454 0.949780 0.946362 0.947961

• 7 0.285500 0.253279 0.948454 0.949780 0.946362 0.947961

• 8 0.326200 0.253156 0.948454 0.949780 0.946362 0.947961

• 9 0.297200 0.253054 0.948454 0.949780 0.946362 0.947961

• 10 0.284200 0.252992 0.948454 0.949780 0.946362 0.947961

• 11 0.289500 0.252961 0.948454 0.949780 0.946362 0.947961

• 12 0.285400 0.252957 0.948454 0.949780 0.946362 0.947961

** TrainOutput(global_step=120, training_loss=0.29438418547312417, metrics={'train_runtime': 253.1978, 'train_samples_per_second': 55.072, 'train_steps_per_second': 0.474, 'total_flos': 716572948593600.0, 'train_loss': 0.29438418547312417, 'epoch': 12.0})