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metadata
license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: distilbert-base-uncased-date
    results: []

distilbert-base-uncased-date

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: 0.2773
  • Precision: 0.0
  • Recall: 0.0
  • F1: 0.0
  • Accuracy: 0.9259

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: 11

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 1.0 1 0.5215 0.0 0.0 0.0 0.9259
No log 2.0 2 0.4264 0.0 0.0 0.0 0.9259
No log 3.0 3 0.3649 0.0 0.0 0.0 0.9259
No log 4.0 4 0.3289 0.0 0.0 0.0 0.9259
No log 5.0 5 0.3099 0.0 0.0 0.0 0.9259
No log 6.0 6 0.2992 0.0 0.0 0.0 0.9259
No log 7.0 7 0.2920 0.0 0.0 0.0 0.9259
No log 8.0 8 0.2865 0.0 0.0 0.0 0.9259
No log 9.0 9 0.2821 0.0 0.0 0.0 0.9259
No log 10.0 10 0.2790 0.0 0.0 0.0 0.9259
No log 11.0 11 0.2773 0.0 0.0 0.0 0.9259

Framework versions

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