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End of training
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metadata
license: apache-2.0
base_model: sentence-transformers/paraphrase-MiniLM-L3-v2
tags:
  - generated_from_trainer
datasets:
  - nyt_ingredients
model-index:
  - name: nyt_ingredients-crf-tagger-paraphrase-MiniLM-L3-v2
    results: []

nyt_ingredients-crf-tagger-paraphrase-MiniLM-L3-v2

This model is a fine-tuned version of sentence-transformers/paraphrase-MiniLM-L3-v2 on the nyt_ingredients dataset. It achieves the following results on the evaluation set:

  • Loss: 10.2590
  • Comment: {'precision': 0.03657262277951933, 'recall': 0.0264750378214826, 'f1': 0.030715225976305396, 'number': 1322}
  • Name: {'precision': 0.5238095238095238, 'recall': 0.01245753114382786, 'f1': 0.024336283185840708, 'number': 1766}
  • Qty: {'precision': 0.0234375, 'recall': 0.0020920502092050207, 'f1': 0.003841229193341869, 'number': 1434}
  • Range End: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 17}
  • Unit: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1166}
  • Overall Precision: 0.0419
  • Overall Recall: 0.0105
  • Overall F1: 0.0168
  • Overall Accuracy: 0.1284

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: 5e-05
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 2

Training results

Training Loss Epoch Step Validation Loss Comment Name Qty Range End Unit Overall Precision Overall Recall Overall F1 Overall Accuracy
No log 1.0 54 11.5992 {'precision': 0.03826530612244898, 'recall': 0.0340393343419062, 'f1': 0.036028823058446756, 'number': 1322} {'precision': 0.9047619047619048, 'recall': 0.010758776896942242, 'f1': 0.021264689423614997, 'number': 1766} {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1434} {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 17} {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1166} 0.0526 0.0112 0.0185 0.1319
No log 2.0 108 10.2590 {'precision': 0.03657262277951933, 'recall': 0.0264750378214826, 'f1': 0.030715225976305396, 'number': 1322} {'precision': 0.5238095238095238, 'recall': 0.01245753114382786, 'f1': 0.024336283185840708, 'number': 1766} {'precision': 0.0234375, 'recall': 0.0020920502092050207, 'f1': 0.003841229193341869, 'number': 1434} {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 17} {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1166} 0.0419 0.0105 0.0168 0.1284

Framework versions

  • Transformers 4.34.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.5
  • Tokenizers 0.14.0