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mpnet-multi-agri-classifier

This model is a fine-tuned version of sentence-transformers/paraphrase-multilingual-mpnet-base-v2 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3444
  • Precision Macro: 0.8402
  • Precision Weighted: 0.9196
  • Recall Macro: 0.9042
  • Recall Weighted: 0.9046
  • F1-score: 0.8655
  • Accuracy: 0.9046

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: 6.9e-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
  • lr_scheduler_warmup_steps: 200
  • num_epochs: 5

Training results

Training Loss Epoch Step Validation Loss Precision Macro Precision Weighted Recall Macro Recall Weighted F1-score Accuracy
0.393 1.0 334 0.2938 0.8528 0.9132 0.8773 0.9092 0.8641 0.9092
0.3213 2.0 668 0.3049 0.8299 0.9110 0.8885 0.8966 0.8534 0.8966
0.2591 3.0 1002 0.2561 0.8654 0.9226 0.8937 0.9184 0.8784 0.9184
0.1853 4.0 1336 0.3254 0.8386 0.9190 0.9034 0.9034 0.8641 0.9034
0.1119 5.0 1670 0.3444 0.8402 0.9196 0.9042 0.9046 0.8655 0.9046

Framework versions

  • Transformers 4.35.2
  • Pytorch 1.12.0+cu102
  • Datasets 2.3.2
  • Tokenizers 0.15.0
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