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final_classifications

This model is a fine-tuned version of yhavinga/t5-small-24L-ccmatrix-multi on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1005
  • F1: {'f1': 0.9592760180995475}
  • Precision: {'precision': 0.954954954954955}
  • Recall: {'recall': 0.9636363636363636}

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: 0.0001
  • 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: 6

Training results

Training Loss Epoch Step Validation Loss F1 Precision Recall
No log 1.0 110 0.2362 {'f1': 0.0} {'precision': 0.0} {'recall': 0.0}
No log 2.0 220 0.1164 {'f1': 0.9502262443438914} {'precision': 0.9459459459459459} {'recall': 0.9545454545454546}
No log 3.0 330 0.0832 {'f1': 0.9596412556053813} {'precision': 0.9469026548672567} {'recall': 0.9727272727272728}
No log 4.0 440 0.0918 {'f1': 0.9549549549549549} {'precision': 0.9464285714285714} {'recall': 0.9636363636363636}
0.1554 5.0 550 0.0939 {'f1': 0.9596412556053813} {'precision': 0.9469026548672567} {'recall': 0.9727272727272728}
0.1554 6.0 660 0.1005 {'f1': 0.9592760180995475} {'precision': 0.954954954954955} {'recall': 0.9636363636363636}

Framework versions

  • Transformers 4.40.1
  • Pytorch 2.2.1+cu121
  • Datasets 2.19.0
  • Tokenizers 0.19.1
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