---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: electra-base-ner-food-recipe
  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

This model is a fine-tuned version of [google/electra-base-discriminator](https://huggingface.co/google/electra-base-discriminator) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1889
- Precision: 0.7866
- Recall: 0.8144
- F1: 0.8003
- Accuracy: 0.9558

## 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: 2e-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: 15

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0216        | 2.66  | 2121  | 0.1672          | 0.7858    | 0.8183 | 0.8017 | 0.9575   |
| 0.0237        | 5.33  | 4242  | 0.1744          | 0.7842    | 0.8122 | 0.7980 | 0.9564   |
| 0.0281        | 7.99  | 6363  | 0.1793          | 0.7812    | 0.8148 | 0.7976 | 0.9558   |
| 0.0236        | 10.66 | 8484  | 0.1863          | 0.7923    | 0.8148 | 0.8034 | 0.9567   |
| 0.0246        | 13.32 | 10605 | 0.1881          | 0.7871    | 0.8170 | 0.8018 | 0.9561   |


### Framework versions

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