README.md

---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
- precision
- recall
model-index:
- name: dress-classifier
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# dress-classifier

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- F1: 0.9260
- Loss: 0.3490
- Accuracy: 0.9256
- Precision: 0.9265
- Recall: 0.9256

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | F1     | Validation Loss | Accuracy | Precision | Recall |
|:-------------:|:-----:|:----:|:------:|:---------------:|:--------:|:---------:|:------:|
| No log        | 1.0   | 269  | 0.8817 | 0.2965          | 0.8940   | 0.8942    | 0.8940 |
| 0.3442        | 2.0   | 538  | 0.9133 | 0.2740          | 0.9163   | 0.9133    | 0.9163 |
| 0.3442        | 3.0   | 807  | 0.9096 | 0.2904          | 0.9060   | 0.9174    | 0.9060 |
| 0.1397        | 4.0   | 1076 | 0.9231 | 0.3103          | 0.9237   | 0.9227    | 0.9237 |
| 0.1397        | 5.0   | 1345 | 0.9260 | 0.3490          | 0.9256   | 0.9265    | 0.9256 |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1