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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: electra-large-discriminator-ner-food-combined-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-large-discriminator-ner-food-combined-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: 0.0754
- Precision: 0.8634
- Recall: 0.8838
- F1: 0.8735
- Accuracy: 0.9760
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1052 | 1.12 | 500 | 0.0754 | 0.8634 | 0.8838 | 0.8735 | 0.9760 |
| 0.0682 | 2.25 | 1000 | 0.0774 | 0.8468 | 0.8972 | 0.8712 | 0.9747 |
| 0.0589 | 3.37 | 1500 | 0.0765 | 0.8731 | 0.8705 | 0.8718 | 0.9756 |
| 0.0527 | 4.49 | 2000 | 0.0796 | 0.8669 | 0.8705 | 0.8687 | 0.9751 |
### Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
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