---
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: text-distilbert-clothes-predictor
  results: []
datasets:
- danjung9/24679-Project1-aug
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# text-distilbert-clothes-predictor

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/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