metadata
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: []
fairhousing-bert-tiny
This model is a fine-tuned version of 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