---
library_name: transformers
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
- f1
model-index:
- name: signet
  results:
  - task:
      type: image-classification
      name: Image Classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: train
      args: default
    metrics:
    - type: accuracy
      value: 0.7853930177768259
      name: Accuracy
    - type: f1
      value: 0.8643011917659805
      name: F1
---

<!-- 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. -->

# signet

This model is a fine-tuned version of [](https://huggingface.co/) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4517
- Accuracy: 0.7854
- F1: 0.8643

## 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: 0.0002
- train_batch_size: 128
- eval_batch_size: 256
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 512
- 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_steps: 0.05
- num_epochs: 12
- mixed_precision_training: Native AMP
- label_smoothing_factor: 0.05

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 37   | 0.5892          | 0.7383   | 0.8479 |
| No log        | 2.0   | 74   | 0.5829          | 0.7372   | 0.8464 |
| 2.4270        | 3.0   | 111  | 0.5547          | 0.7419   | 0.8504 |
| 2.4270        | 4.0   | 148  | 0.5311          | 0.7344   | 0.8415 |
| 2.4270        | 5.0   | 185  | 0.5291          | 0.7404   | 0.8472 |
| 2.1988        | 6.0   | 222  | 0.5170          | 0.7432   | 0.8496 |
| 2.1988        | 7.0   | 259  | 0.4517          | 0.7854   | 0.8643 |
| 2.1988        | 8.0   | 296  | 0.4865          | 0.7653   | 0.8406 |
| 1.9616        | 9.0   | 333  | 0.4380          | 0.7875   | 0.8614 |
| 1.9616        | 10.0  | 370  | 0.4546          | 0.7698   | 0.8367 |
| 1.7220        | 11.0  | 407  | 0.4355          | 0.7901   | 0.8552 |
| 1.7220        | 12.0  | 444  | 0.4334          | 0.7963   | 0.8622 |


### Framework versions

- Transformers 5.0.0
- Pytorch 2.9.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2