distrilbert_full_parameter_finetune_crisismmd

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

  • Loss: 0.3472
  • Accuracy: 84.87%
  • Precision: 84.73%
  • Recall: 84.87%
  • F1: 84.42%

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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • num_epochs: 1

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision Recall F1
0.5759 0.0482 50 0.4439 80.61% 80.68% 80.61% 80.64%
0.4797 0.0964 100 0.4242 81.50% 81.28% 81.50% 80.67%
0.4362 0.1446 150 0.4136 82.77% 82.97% 82.77% 82.86%
0.4631 0.1929 200 0.4900 81.25% 82.43% 81.25% 79.54%
0.4326 0.2411 250 0.4333 83.28% 83.86% 83.28% 82.20%
0.3911 0.2893 300 0.4526 82.45% 83.21% 82.45% 81.17%
0.4426 0.3375 350 0.4395 83.22% 84.14% 83.22% 83.48%
0.4022 0.3857 400 0.3950 83.47% 83.21% 83.47% 83.25%
0.3937 0.4339 450 0.3667 84.55% 84.36% 84.55% 84.42%
0.3773 0.4822 500 0.3843 84.74% 84.53% 84.74% 84.38%
0.451 0.5304 550 0.3858 82.52% 83.49% 82.52% 81.15%
0.3488 0.5786 600 0.3840 84.68% 84.54% 84.68% 84.21%
0.3773 0.6268 650 0.3851 84.23% 84.27% 84.23% 83.57%
0.3442 0.6750 700 0.3492 85.31% 85.10% 85.31% 85.08%
0.3348 0.7232 750 0.4122 84.11% 84.64% 84.11% 83.17%
0.4304 0.7715 800 0.3499 84.81% 84.80% 84.81% 84.24%
0.3724 0.8197 850 0.3569 84.87% 84.81% 84.87% 84.34%
0.3212 0.8679 900 0.3706 84.62% 84.86% 84.62% 83.88%
0.4108 0.9161 950 0.3835 84.23% 84.65% 84.23% 83.36%
0.3334 0.9643 1000 0.3472 84.87% 84.73% 84.87% 84.42%

Framework versions

  • Transformers 4.50.3
  • Pytorch 2.6.0+cu124
  • Datasets 3.5.0
  • Tokenizers 0.21.1
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