---
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: []
---

<!-- 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](https://huggingface.co/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