---
library_name: transformers
license: apache-2.0
base_model: google/bert_uncased_L-2_H-128_A-2
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: fairhousing-bert-tiny
  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. -->

# fairhousing-bert-tiny

This model is a fine-tuned version of [google/bert_uncased_L-2_H-128_A-2](https://huggingface.co/google/bert_uncased_L-2_H-128_A-2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0148
- Accuracy: 1.0
- Precision: 1.0
- Recall: 1.0
- F1: 1.0

## 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: 16
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.4076        | 1.0   | 474  | 0.2490          | 0.9852   | 0.9970    | 0.9842 | 0.9906 |
| 0.0284        | 2.0   | 948  | 0.0148          | 1.0      | 1.0       | 1.0    | 1.0    |
| 0.0116        | 3.0   | 1422 | 0.0063          | 1.0      | 1.0       | 1.0    | 1.0    |
| 0.0104        | 4.0   | 1896 | 0.0043          | 1.0      | 1.0       | 1.0    | 1.0    |
| 0.005         | 5.0   | 2370 | 0.0038          | 1.0      | 1.0       | 1.0    | 1.0    |


### Framework versions

- Transformers 4.55.0
- Pytorch 2.8.0
- Datasets 4.0.0
- Tokenizers 0.21.4