---
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
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# 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: 0.3833
- Precision: 0.7056
- Recall: 0.7083
- F1: 0.7067
- Accuracy: 0.9413

## 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2989        | 1.0   | 2500 | 0.4197          | 0.6917    | 0.6943 | 0.6919 | 0.9216   |
| 0.2046        | 2.0   | 5000 | 0.4013          | 0.7029    | 0.7052 | 0.7035 | 0.9368   |
| 0.1039        | 3.0   | 7500 | 0.3833          | 0.7056    | 0.7083 | 0.7067 | 0.9413   |


### Framework versions

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