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

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tlogandesigns/fairhousing-bert-tiny

fairhousing-bert-tiny

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

fairhousing-bert-tiny

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions