damage_trigger_effect_2023-12-18_15_20

This model is a fine-tuned version of DeepPavlov/bert-base-bg-cs-pl-ru-cased on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5807
  • Precision: 0.0
  • Recall: 0.0
  • F1: 0.0
  • Accuracy: 0.8588

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 Precision Recall F1 Accuracy
No log 1.0 34 0.5744 0.0 0.0 0.0 0.8099
No log 2.0 68 0.4567 0.0 0.0 0.0 0.8393
No log 3.0 102 0.4566 0.0 0.0 0.0 0.8474
No log 4.0 136 0.4308 0.0 0.0 0.0 0.8585
No log 5.0 170 0.4606 0.0 0.0 0.0 0.8422
No log 6.0 204 0.4777 0.0 0.0 0.0 0.8510
No log 7.0 238 0.4681 0.0 0.0 0.0 0.8569
No log 8.0 272 0.5150 0.0 0.0 0.0 0.8523
No log 9.0 306 0.4945 0.0 0.0 0.0 0.8650
No log 10.0 340 0.5582 0.0 0.0 0.0 0.8533
No log 11.0 374 0.5274 0.0 0.0 0.0 0.8591
No log 12.0 408 0.5547 0.0 0.0 0.0 0.8595
No log 13.0 442 0.5707 0.0 0.0 0.0 0.8598
No log 14.0 476 0.5814 0.0 0.0 0.0 0.8549
0.2474 15.0 510 0.5807 0.0 0.0 0.0 0.8588

Framework versions

  • Transformers 4.36.1
  • Pytorch 2.1.0+cu121
  • Datasets 2.15.0
  • Tokenizers 0.15.0
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