---
base_model: microsoft/codebert-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: codebert-base-password-strength-classifier-normal-weight-balancing
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# codebert-base-password-strength-classifier-normal-weight-balancing

This model is a fine-tuned version of [microsoft/codebert-base](https://huggingface.co/microsoft/codebert-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0083
- Accuracy: 0.9977
- Weighted f1: 0.9977
- Micro f1: 0.9977
- Macro f1: 0.9966
- Weighted recall: 0.9977
- Micro recall: 0.9977
- Macro recall: 0.9979
- Weighted precision: 0.9977
- Micro precision: 0.9977
- Macro precision: 0.9953

## 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: 2

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Weighted f1 | Micro f1 | Macro f1 | Weighted recall | Micro recall | Macro recall | Weighted precision | Micro precision | Macro precision |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:-----------:|:--------:|:--------:|:---------------:|:------------:|:------------:|:------------------:|:---------------:|:---------------:|
| 0.0345        | 1.0   | 37667 | 0.0522          | 0.9825   | 0.9829      | 0.9825   | 0.9755   | 0.9825          | 0.9825       | 0.9915       | 0.9844             | 0.9825          | 0.9619          |
| 0.0099        | 2.0   | 75334 | 0.0083          | 0.9977   | 0.9977      | 0.9977   | 0.9966   | 0.9977          | 0.9977       | 0.9979       | 0.9977             | 0.9977          | 0.9953          |


### Framework versions

- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.6.dev0
- Tokenizers 0.13.3