CoolFace
Modelpublic

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

sourceHugging Faceapache-2.0updated 3y agoView on Hugging Face
0likes6downloads
Model Card

<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->

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: 11.3870
  • —Comment: {'precision': 0.018842530282637954, 'recall': 0.010174418604651164, 'f1': 0.01321378008494573, 'number': 1376}
  • —Name: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1758}
  • —Qty: {'precision': 0.1499119991717569, 'recall': 0.9986206896551724, 'f1': 0.26068953101089204, 'number': 1450}
  • —Range End: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 14}
  • —Unit: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1163}
  • —Overall Precision: 0.1405
  • —Overall Recall: 0.2538
  • —Overall F1: 0.1809
  • —Overall Accuracy: 0.1528

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
  • —trainbatchsize: 32
  • —evalbatchsize: 32
  • —seed: 42
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: linear
  • —num_epochs: 2

Training results

Training LossEpochStepValidation LossCommentNameQtyRange EndUnitOverall PrecisionOverall RecallOverall F1Overall Accuracy
No log1.05413.0360{'precision': 0.003246753246753247, 'recall': 0.0007267441860465116, 'f1': 0.001187648456057007, 'number': 1376}{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1758}{'precision': 0.142309205350118, 'recall': 0.9979310344827587, 'f1': 0.24909622998794975, 'number': 1450}{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 14}{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1163}0.13820.25130.17840.1432
No log2.010811.3870{'precision': 0.018842530282637954, 'recall': 0.010174418604651164, 'f1': 0.01321378008494573, 'number': 1376}{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1758}{'precision': 0.1499119991717569, 'recall': 0.9986206896551724, 'f1': 0.26068953101089204, 'number': 1450}{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 14}{'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1163}0.14050.25380.18090.1528

Framework versions

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