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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_bert-base-uncased
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_bert-base-uncased
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: 0.5398
- Accuracy: 0.8705
- F1: 0.8691
- Precision: 0.8729
- Recall: 0.8705
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.9217 | 1.0 | 91 | 0.8648 | 0.6459 | 0.5998 | 0.6333 | 0.6459 |
| 0.5726 | 2.0 | 182 | 0.5369 | 0.8066 | 0.8064 | 0.8238 | 0.8066 |
| 0.3522 | 3.0 | 273 | 0.4095 | 0.8440 | 0.8415 | 0.8477 | 0.8440 |
| 0.2589 | 4.0 | 364 | 0.5367 | 0.8097 | 0.8069 | 0.8258 | 0.8097 |
| 0.2718 | 5.0 | 455 | 0.4216 | 0.8612 | 0.8621 | 0.8670 | 0.8612 |
| 0.164 | 6.0 | 546 | 0.5346 | 0.8612 | 0.8602 | 0.8616 | 0.8612 |
| 0.1075 | 7.0 | 637 | 0.5398 | 0.8705 | 0.8691 | 0.8729 | 0.8705 |
| 0.1461 | 8.0 | 728 | 0.6163 | 0.8362 | 0.8368 | 0.8442 | 0.8362 |
| 0.132 | 9.0 | 819 | 0.4933 | 0.8674 | 0.8675 | 0.8701 | 0.8674 |
| 0.1359 | 10.0 | 910 | 0.7141 | 0.8424 | 0.8416 | 0.8489 | 0.8424 |
| 0.0971 | 11.0 | 1001 | 0.5662 | 0.8596 | 0.8578 | 0.8623 | 0.8596 |
| 0.1148 | 12.0 | 1092 | 0.5685 | 0.8612 | 0.8609 | 0.8610 | 0.8612 |
### Framework versions
- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.1
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