---
license: apache-2.0
base_model: microsoft/resnet-18
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: font-identifier
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: test
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.7810232220609579
---

<!-- 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. -->

# font-identifier

This model is a fine-tuned version of [microsoft/resnet-18](https://huggingface.co/microsoft/resnet-18) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8935
- Accuracy: 0.7810

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 7.2836        | 1.0   | 344   | 7.2178          | 0.0038   |
| 6.6696        | 2.0   | 689   | 6.4685          | 0.0408   |
| 5.85          | 3.0   | 1034  | 5.3897          | 0.1254   |
| 5.0457        | 4.0   | 1379  | 4.4771          | 0.2143   |
| 4.3784        | 5.0   | 1723  | 3.6429          | 0.3242   |
| 3.809         | 6.0   | 2068  | 3.1236          | 0.4031   |
| 3.4229        | 7.0   | 2413  | 2.6388          | 0.4672   |
| 2.8977        | 8.0   | 2758  | 2.3279          | 0.5102   |
| 2.78          | 9.0   | 3102  | 2.0974          | 0.5682   |
| 2.4452        | 10.0  | 3447  | 1.8605          | 0.6027   |
| 2.2195        | 11.0  | 3792  | 1.6783          | 0.6312   |
| 2.1097        | 12.0  | 4137  | 1.6049          | 0.6390   |
| 1.9025        | 13.0  | 4481  | 1.4255          | 0.6912   |
| 1.7973        | 14.0  | 4826  | 1.3253          | 0.7075   |
| 1.7647        | 15.0  | 5171  | 1.3030          | 0.7032   |
| 1.6772        | 16.0  | 5516  | 1.1988          | 0.7210   |
| 1.5523        | 17.0  | 5860  | 1.1040          | 0.7395   |
| 1.4821        | 18.0  | 6205  | 1.0786          | 0.7380   |
| 1.3764        | 19.0  | 6550  | 1.0603          | 0.7471   |
| 1.2913        | 20.0  | 6895  | 1.0169          | 0.7542   |
| 1.3479        | 21.0  | 7239  | 0.9999          | 0.7563   |
| 1.3133        | 22.0  | 7584  | 0.9928          | 0.7594   |
| 1.2241        | 23.0  | 7929  | 0.9342          | 0.7649   |
| 1.1651        | 24.0  | 8274  | 0.9283          | 0.7658   |
| 1.1605        | 25.0  | 8618  | 0.9176          | 0.7720   |
| 1.0283        | 26.0  | 8963  | 0.8970          | 0.7767   |
| 1.1211        | 27.0  | 9308  | 0.8983          | 0.7754   |
| 1.1563        | 28.0  | 9653  | 0.8729          | 0.7801   |
| 1.1399        | 29.0  | 9997  | 0.9021          | 0.7732   |
| 1.1715        | 29.93 | 10320 | 0.8935          | 0.7810   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.0.0
- Datasets 2.15.0
- Tokenizers 0.15.0