---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: electra-base-ner-food-recipe-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. -->

# electra-base-ner-food-recipe-v2

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1709
- Precision: 0.8007
- Recall: 0.8867
- F1: 0.8415
- Accuracy: 0.9669

## 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-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 0.5   | 400  | 0.1420          | 0.7862    | 0.8871 | 0.8336 | 0.9655   |
| 0.101         | 1.01  | 800  | 0.1580          | 0.8317    | 0.8817 | 0.8559 | 0.9716   |
| 0.0966        | 1.51  | 1200 | 0.1467          | 0.8105    | 0.8917 | 0.8492 | 0.9693   |
| 0.0849        | 2.01  | 1600 | 0.1408          | 0.7966    | 0.8771 | 0.8349 | 0.9669   |
| 0.085         | 2.51  | 2000 | 0.1487          | 0.7941    | 0.8880 | 0.8384 | 0.9662   |
| 0.085         | 3.02  | 2400 | 0.1477          | 0.7773    | 0.8867 | 0.8284 | 0.9635   |
| 0.0766        | 3.52  | 2800 | 0.1852          | 0.8298    | 0.8807 | 0.8545 | 0.9710   |
| 0.0725        | 4.02  | 3200 | 0.1674          | 0.8073    | 0.8830 | 0.8435 | 0.9679   |
| 0.069         | 4.52  | 3600 | 0.1709          | 0.8007    | 0.8867 | 0.8415 | 0.9669   |


### Framework versions

- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3