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---
license: apache-2.0
base_model: google/electra-base-discriminator
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: electra-base-discriminator-finetuned-detests
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-finetuned-detests
This model is a fine-tuned version of [google/electra-base-discriminator](https://huggingface.co/google/electra-base-discriminator) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1215
- Accuracy: 0.7807
- F1-score: 0.7308
- Precision: 0.7162
- Recall: 0.7768
- Auc: 0.7768
## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1-score | Precision | Recall | Auc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|:------:|:------:|
| 0.3236 | 1.0 | 174 | 0.4661 | 0.7610 | 0.6684 | 0.6647 | 0.6728 | 0.6728 |
| 0.3239 | 2.0 | 348 | 0.4287 | 0.7987 | 0.7144 | 0.7138 | 0.7149 | 0.7149 |
| 0.3421 | 3.0 | 522 | 0.5586 | 0.7741 | 0.7292 | 0.7163 | 0.7853 | 0.7853 |
| 0.2288 | 4.0 | 696 | 0.6229 | 0.7807 | 0.7308 | 0.7162 | 0.7768 | 0.7768 |
| 0.1888 | 5.0 | 870 | 0.6629 | 0.7954 | 0.7293 | 0.7173 | 0.7483 | 0.7483 |
| 0.2205 | 6.0 | 1044 | 0.8462 | 0.8036 | 0.7349 | 0.7251 | 0.7485 | 0.7485 |
| 0.1512 | 7.0 | 1218 | 0.8362 | 0.8151 | 0.7335 | 0.7367 | 0.7306 | 0.7306 |
| 0.2345 | 8.0 | 1392 | 1.0372 | 0.7758 | 0.7204 | 0.7063 | 0.7584 | 0.7584 |
| 0.0592 | 9.0 | 1566 | 1.0396 | 0.7840 | 0.7291 | 0.7142 | 0.7663 | 0.7663 |
| 0.0381 | 10.0 | 1740 | 1.1215 | 0.7807 | 0.7308 | 0.7162 | 0.7768 | 0.7768 |
### Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
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