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metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
  - generated_from_trainer
metrics:
  - f1
  - accuracy
model-index:
  - name: reporting-multiclass
    results: []

reporting-multiclass

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: 0.1098
  • F1: 1.0
  • Roc Auc: 1.0
  • Accuracy: 1.0

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: 8
  • eval_batch_size: 8
  • 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 Roc Auc Accuracy
0.5931 1.0 33 0.4546 0.3988 0.6313 0.0
0.4492 2.0 66 0.3765 0.4629 0.6625 0.0446
0.3941 3.0 99 0.3113 0.6222 0.7403 0.0893
0.3004 4.0 132 0.2589 0.7948 0.8383 0.375
0.2581 5.0 165 0.2200 0.8741 0.8935 0.6071
0.2375 6.0 198 0.1922 0.9129 0.9302 0.6875
0.1881 7.0 231 0.1711 0.9333 0.9375 0.75
0.1806 8.0 264 0.1546 0.9390 0.9456 0.7857
0.164 9.0 297 0.1412 0.9654 0.9665 0.8661
0.1466 10.0 330 0.1309 0.9654 0.9665 0.8661
0.1318 11.0 363 0.1229 0.9772 0.9777 0.9107
0.13 12.0 396 0.1169 0.9933 0.9933 0.9732
0.1225 13.0 429 0.1129 1.0 1.0 1.0
0.1165 14.0 462 0.1106 1.0 1.0 1.0
0.1215 15.0 495 0.1098 1.0 1.0 1.0

Framework versions

  • Transformers 4.42.4
  • Pytorch 2.3.1+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1