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

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: 0.3857
- Precision: 0.7092
- Recall: 0.7122
- F1: 0.7105
- Accuracy: 0.9463

## 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: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.385         | 1.0   | 2500  | 0.4128          | 0.6909    | 0.6936 | 0.6910 | 0.9204   |
| 0.2798        | 2.0   | 5000  | 0.4055          | 0.6934    | 0.6951 | 0.6934 | 0.9234   |
| 0.2032        | 3.0   | 7500  | 0.3651          | 0.7042    | 0.7064 | 0.7052 | 0.9392   |
| 0.1438        | 4.0   | 10000 | 0.4059          | 0.7055    | 0.7089 | 0.7069 | 0.9416   |
| 0.0829        | 5.0   | 12500 | 0.3857          | 0.7092    | 0.7122 | 0.7105 | 0.9463   |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1