---
license: apache-2.0
base_model: google/electra-base-discriminator
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: electra-finetuned-ner-S800
  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-finetuned-ner-S800

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: 0.0697
- Precision: 0.6146
- Recall: 0.7181
- F1: 0.6624
- Accuracy: 0.9758

## 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-05
- 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        | 1.0   | 55   | 0.1115          | 0.4736    | 0.5161 | 0.4940 | 0.9552   |
| No log        | 2.0   | 110  | 0.0765          | 0.5789    | 0.6690 | 0.6207 | 0.9721   |
| No log        | 3.0   | 165  | 0.0711          | 0.5671    | 0.7055 | 0.6288 | 0.9730   |
| No log        | 4.0   | 220  | 0.0698          | 0.6266    | 0.7083 | 0.6649 | 0.9753   |
| No log        | 5.0   | 275  | 0.0697          | 0.6146    | 0.7181 | 0.6624 | 0.9758   |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3