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---
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
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