---
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_flang-bert
  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_flang-bert

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: 0.4214
- Accuracy: 0.8830
- F1: 0.8826
- Precision: 0.8829
- Recall: 0.8830

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.9314        | 1.0   | 91   | 0.8698          | 0.6318   | 0.5743 | 0.6153    | 0.6318 |
| 0.541         | 2.0   | 182  | 0.4762          | 0.8237   | 0.8247 | 0.8338    | 0.8237 |
| 0.3217        | 3.0   | 273  | 0.3709          | 0.8580   | 0.8577 | 0.8576    | 0.8580 |
| 0.2774        | 4.0   | 364  | 0.4027          | 0.8596   | 0.8582 | 0.8589    | 0.8596 |
| 0.2154        | 5.0   | 455  | 0.4351          | 0.8424   | 0.8437 | 0.8537    | 0.8424 |
| 0.1525        | 6.0   | 546  | 0.4732          | 0.8487   | 0.8459 | 0.8492    | 0.8487 |
| 0.1429        | 7.0   | 637  | 0.4214          | 0.8830   | 0.8826 | 0.8829    | 0.8830 |
| 0.1074        | 8.0   | 728  | 0.5150          | 0.8674   | 0.8678 | 0.8695    | 0.8674 |
| 0.1323        | 9.0   | 819  | 0.5122          | 0.8705   | 0.8697 | 0.8708    | 0.8705 |
| 0.117         | 10.0  | 910  | 0.7296          | 0.8268   | 0.8245 | 0.8294    | 0.8268 |
| 0.1041        | 11.0  | 1001 | 0.5587          | 0.8643   | 0.8620 | 0.8648    | 0.8643 |
| 0.0598        | 12.0  | 1092 | 0.6548          | 0.8565   | 0.8564 | 0.8565    | 0.8565 |


### Framework versions

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