ec_classfication / README.md
kimsiun's picture
update model card README.md
ab9b88a
metadata
license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - f1
model-index:
  - name: ec_classfication
    results: []

ec_classfication

This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6543
  • F1: 0.7609

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: 1e-05
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 15

Training results

Training Loss Epoch Step Validation Loss F1
No log 1.0 31 0.6418 0.4262
No log 2.0 62 0.4992 0.7342
No log 3.0 93 0.4732 0.7879
No log 4.0 124 0.4817 0.7089
No log 5.0 155 0.4872 0.7742
No log 6.0 186 0.5026 0.7872
No log 7.0 217 0.5202 0.7778
No log 8.0 248 0.5280 0.7711
No log 9.0 279 0.5629 0.75
No log 10.0 310 0.6319 0.7872
No log 11.0 341 0.6363 0.7872
No log 12.0 372 0.6850 0.7708
No log 13.0 403 0.6702 0.7872
No log 14.0 434 0.6495 0.7692
No log 15.0 465 0.6543 0.7609

Framework versions

  • Transformers 4.27.3
  • Pytorch 2.0.0+cu118
  • Datasets 2.11.0
  • Tokenizers 0.13.2