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

This model is a fine-tuned version of [google/electra-base-discriminator](https://huggingface.co/google/electra-base-discriminator) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2211
- Accuracy: 0.9267
- F1: 0.9267
- Precision: 0.9267
- Recall: 0.9267

## 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: 0.0001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 25

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.932         | 1.0   | 91   | 0.8735          | 0.6412   | 0.5915 | 0.6417    | 0.6412 |
| 0.426         | 2.0   | 182  | 0.3389          | 0.9002   | 0.9004 | 0.9008    | 0.9002 |
| 0.259         | 3.0   | 273  | 0.2577          | 0.9048   | 0.9039 | 0.9070    | 0.9048 |
| 0.1619        | 4.0   | 364  | 0.2211          | 0.9267   | 0.9267 | 0.9267    | 0.9267 |
| 0.1574        | 5.0   | 455  | 0.3301          | 0.8955   | 0.8959 | 0.9045    | 0.8955 |
| 0.0929        | 6.0   | 546  | 0.3284          | 0.9064   | 0.9054 | 0.9066    | 0.9064 |
| 0.1079        | 7.0   | 637  | 0.3467          | 0.9002   | 0.9003 | 0.9040    | 0.9002 |
| 0.0927        | 8.0   | 728  | 0.3817          | 0.9002   | 0.8993 | 0.9056    | 0.9002 |
| 0.0876        | 9.0   | 819  | 0.3524          | 0.9048   | 0.9044 | 0.9047    | 0.9048 |


### Framework versions

- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.1