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---
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_roberta-base
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_roberta-base
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: 0.4180
- Accuracy: 0.8768
- F1: 0.8767
- Precision: 0.8766
- Recall: 0.8768
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.955 | 1.0 | 91 | 0.8849 | 0.6349 | 0.5849 | 0.6173 | 0.6349 |
| 0.4845 | 2.0 | 182 | 0.4777 | 0.8237 | 0.8221 | 0.8271 | 0.8237 |
| 0.3434 | 3.0 | 273 | 0.3821 | 0.8580 | 0.8579 | 0.8598 | 0.8580 |
| 0.2683 | 4.0 | 364 | 0.5158 | 0.8237 | 0.8213 | 0.8362 | 0.8237 |
| 0.1675 | 5.0 | 455 | 0.3875 | 0.8643 | 0.8633 | 0.8651 | 0.8643 |
| 0.1788 | 6.0 | 546 | 0.4180 | 0.8768 | 0.8767 | 0.8766 | 0.8768 |
| 0.1669 | 7.0 | 637 | 0.4189 | 0.8768 | 0.8754 | 0.8775 | 0.8768 |
| 0.1103 | 8.0 | 728 | 0.5338 | 0.8534 | 0.8542 | 0.8569 | 0.8534 |
| 0.1597 | 9.0 | 819 | 0.4306 | 0.8674 | 0.8674 | 0.8676 | 0.8674 |
| 0.1443 | 10.0 | 910 | 0.6446 | 0.8580 | 0.8574 | 0.8580 | 0.8580 |
| 0.1012 | 11.0 | 1001 | 0.5104 | 0.8534 | 0.8535 | 0.8541 | 0.8534 |
### Framework versions
- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.1
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