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sentic-singletTextWcBerta-Fold1

This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5627
  • Accuracy: 0.7510
  • Precision: 0.7401
  • Recall: 0.7510
  • F1 Score: 0.7431

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: 1e-05
  • train_batch_size: 64
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • num_epochs: 15

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision Recall F1 Score
No log 1.0 60 0.6901 0.7040 0.7917 0.7040 0.5827
0.501 2.0 120 0.5192 0.7354 0.7138 0.7354 0.6994
0.501 3.0 180 0.5411 0.7270 0.7045 0.7270 0.7048
0.4839 4.0 240 0.8009 0.7029 0.6429 0.7029 0.5822
0.4849 5.0 300 0.5294 0.7374 0.7163 0.7374 0.7066
0.4849 6.0 360 0.5430 0.7301 0.7109 0.7301 0.7132
0.4684 7.0 420 0.5570 0.7312 0.7104 0.7312 0.7110
0.4684 8.0 480 0.5740 0.7416 0.7258 0.7416 0.7006
0.4182 9.0 540 0.6109 0.7458 0.7328 0.7458 0.7054
0.4052 10.0 600 0.5607 0.7490 0.7357 0.7490 0.7383
0.4052 11.0 660 0.5974 0.7510 0.7369 0.7510 0.7182
0.3884 12.0 720 0.5715 0.7333 0.7423 0.7333 0.7370
0.3884 13.0 780 0.5603 0.7552 0.7463 0.7552 0.7492
0.364 14.0 840 0.5610 0.7573 0.7511 0.7573 0.7535
0.3564 15.0 900 0.5627 0.7510 0.7401 0.7510 0.7431

Framework versions

  • Transformers 4.44.0
  • Pytorch 2.4.0
  • Datasets 2.21.0
  • Tokenizers 0.19.1
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