README.md

---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: electra-large-discriminator-ner-food-combined-weighted-v2
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# electra-large-discriminator-ner-food-combined-weighted-v2

This model is a fine-tuned version of [google/electra-large-discriminator](https://huggingface.co/google/electra-large-discriminator) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1185
- Precision: 0.7681
- Recall: 0.8893
- F1: 0.8242
- Accuracy: 0.9630

## 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: 16
- eval_batch_size: 24
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1326        | 1.12  | 500  | 0.1213          | 0.7978    | 0.8984 | 0.8451 | 0.9691   |
| 0.1059        | 2.25  | 1000 | 0.1185          | 0.7681    | 0.8893 | 0.8242 | 0.9630   |
| 0.1109        | 3.37  | 1500 | 0.1378          | 0.7766    | 0.8784 | 0.8244 | 0.9592   |
| 0.0907        | 4.49  | 2000 | 0.1279          | 0.7791    | 0.8897 | 0.8307 | 0.9642   |
| 0.0732        | 5.62  | 2500 | 0.1521          | 0.7933    | 0.8918 | 0.8397 | 0.9669   |


### Framework versions

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