my_awesome_model / README.md
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metadata
license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
model-index:
  - name: my_awesome_model
    results: []

my_awesome_model

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: 1.0970
  • Accuracy: 0.8681
  • F1: 0.8376

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: 15

Training results

Training Loss Epoch Step Validation Loss Accuracy F1
No log 1.0 167 0.3828 0.8501 0.8031
No log 2.0 334 0.4787 0.8456 0.8275
0.2101 3.0 501 0.6186 0.8666 0.8367
0.2101 4.0 668 0.7201 0.8546 0.8265
0.2101 5.0 835 0.7675 0.8651 0.8346
0.0339 6.0 1002 0.8561 0.8681 0.8434
0.0339 7.0 1169 0.8898 0.8681 0.8382
0.0339 8.0 1336 0.9854 0.8711 0.8436
0.0069 9.0 1503 0.9919 0.8711 0.8407
0.0069 10.0 1670 1.0695 0.8561 0.8280
0.0069 11.0 1837 1.0542 0.8666 0.8349
0.0007 12.0 2004 1.0896 0.8681 0.8370
0.0007 13.0 2171 1.1001 0.8666 0.8349
0.0007 14.0 2338 1.0888 0.8606 0.8312
0.0012 15.0 2505 1.0970 0.8681 0.8376

Framework versions

  • Transformers 4.29.2
  • Pytorch 2.0.1+cu118
  • Datasets 2.12.0
  • Tokenizers 0.13.3