metadata
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
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