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metadata
license: apache-2.0
base_model: sentence-transformers/LaBSE
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: binary_persian_sentiment_analysis
    results: []

binary_persian_sentiment_analysis

This model is a fine-tuned version of sentence-transformers/LaBSE on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5060
  • Accuracy: 0.8805
  • F1 Score: 0.8805

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: 2
  • eval_batch_size: 2
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy F1 Score
0.5045 1.0 8359 0.5295 0.8816 0.8814
0.4211 2.0 16718 0.6029 0.8837 0.8837
0.3501 3.0 25077 0.5060 0.8805 0.8805
0.2541 4.0 33436 0.7740 0.8762 0.8762
0.2065 5.0 41795 0.8071 0.8746 0.8745
0.1915 6.0 50154 0.8341 0.8805 0.8805
0.137 7.0 58513 0.9235 0.8644 0.8644
0.0605 8.0 66872 0.9695 0.8584 0.8584
0.0405 9.0 75231 1.0090 0.8751 0.8751
0.0712 10.0 83590 1.0134 0.8767 0.8767
0.0295 11.0 91949 1.0266 0.8708 0.8709
0.0704 12.0 100308 0.9940 0.8767 0.8767
0.0233 13.0 108667 1.0747 0.8762 0.8762
0.0153 14.0 117026 1.0747 0.8741 0.8741
0.0245 15.0 125385 1.0027 0.8837 0.8837
0.0618 16.0 133744 0.9939 0.8778 0.8778
0.0087 17.0 142103 1.0448 0.8854 0.8853
0.0174 18.0 150462 1.0339 0.8837 0.8838
0.0185 19.0 158821 1.1171 0.8778 0.8778
0.0075 20.0 167180 1.1022 0.8827 0.8827

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.16.1
  • Tokenizers 0.15.0