text-distilbert-clothes-predictor

This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.0001
• Accuracy: 1.0
• F1: 1.0
• Precision: 1.0
• Recall: 1.0

Model description

This a DistilBERT model that is trained on a clothing dataset (see Training and evaluation data section). It is used to classify whether a piece of wear is business casual.

Intended uses & limitations

Educational purposes. Dataset might not be big enough (as inferred by the result).

Training and evaluation data

Source: https://huggingface.co/datasets/danjung9/24679-Project1-aug

(train/val/test) = (64/16/20)

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 2e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• 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
• num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.0001	1.0	800	0.0001	1.0	1.0	1.0	1.0
0.0	2.0	1600	0.0000	1.0	1.0	1.0	1.0
0.0	3.0	2400	0.0000	1.0	1.0	1.0	1.0
0.0	4.0	3200	0.0000	1.0	1.0	1.0	1.0
0.0	5.0	4000	0.0000	1.0	1.0	1.0	1.0

Framework versions

• Transformers 4.56.2
• Pytorch 2.8.0+cu126
• Datasets 4.0.0
• Tokenizers 0.22.0