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

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: 0.1500
- Precision: 0.7191
- Recall: 0.8739
- F1: 0.7890
- Accuracy: 0.9568

## 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-07
- 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  | 0.4360          | 0.4354    | 0.7533 | 0.5519 | 0.8775   |
| 0.5627        | 1.01  | 800  | 0.2274          | 0.6971    | 0.8525 | 0.7670 | 0.9508   |
| 0.2799        | 1.51  | 1200 | 0.1791          | 0.6728    | 0.8762 | 0.7612 | 0.9492   |
| 0.1983        | 2.01  | 1600 | 0.1652          | 0.6958    | 0.8757 | 0.7755 | 0.9535   |
| 0.1821        | 2.51  | 2000 | 0.1610          | 0.7171    | 0.8766 | 0.7889 | 0.9568   |
| 0.1821        | 3.02  | 2400 | 0.1550          | 0.7001    | 0.8757 | 0.7782 | 0.9539   |
| 0.1726        | 3.52  | 2800 | 0.1537          | 0.7211    | 0.8744 | 0.7904 | 0.9573   |
| 0.1674        | 4.02  | 3200 | 0.1510          | 0.7170    | 0.8739 | 0.7877 | 0.9565   |
| 0.1682        | 4.52  | 3600 | 0.1501          | 0.7147    | 0.8744 | 0.7865 | 0.9564   |


### Framework versions

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

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "electra-base-ner-food-recipe-v2", "results": []}]}
transformers pytorch tensorboard electra token-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #electra #token-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

electra-base-ner-food-recipe-v2
===============================


This model is a fine-tuned version of google/electra-base-discriminator on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.1500
* Precision: 0.7191
* Recall: 0.8739
* F1: 0.7890
* Accuracy: 0.9568


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-07
* 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



### Framework versions


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



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-07
* 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 ### Framework versions


* Transformers 4.27.4
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #electra #token-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-07
* 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 ### Framework versions


* Transformers 4.27.4
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #electra #token-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-07
* 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### Framework versions


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