---
library_name: transformers
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: 0.9454545454545454
---

<!-- 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: 0.1706
- Accuracy: 0.9455

## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.2323        | 1.0   | 14   | 3.1711          | 0.05     |
| 3.1019        | 2.0   | 28   | 2.9173          | 0.1227   |
| 2.779         | 3.0   | 42   | 2.5695          | 0.2409   |
| 2.5           | 4.0   | 56   | 2.1142          | 0.4091   |
| 1.8064        | 5.0   | 70   | 1.6804          | 0.4864   |
| 1.575         | 6.0   | 84   | 1.2757          | 0.5773   |
| 1.348         | 7.0   | 98   | 1.0973          | 0.6864   |
| 1.0483        | 8.0   | 112  | 0.8965          | 0.7273   |
| 0.9753        | 9.0   | 126  | 0.7025          | 0.7682   |
| 0.7763        | 10.0  | 140  | 0.6220          | 0.8091   |
| 0.7392        | 11.0  | 154  | 0.5169          | 0.8636   |
| 0.7077        | 12.0  | 168  | 0.4815          | 0.8682   |
| 0.5433        | 13.0  | 182  | 0.4650          | 0.8455   |
| 0.565         | 14.0  | 196  | 0.3828          | 0.8773   |
| 0.4204        | 15.0  | 210  | 0.3493          | 0.8864   |
| 0.4798        | 16.0  | 224  | 0.2847          | 0.9045   |
| 0.4353        | 17.0  | 238  | 0.3370          | 0.8773   |
| 0.3871        | 18.0  | 252  | 0.2797          | 0.9045   |
| 0.3779        | 19.0  | 266  | 0.2671          | 0.9045   |
| 0.3819        | 20.0  | 280  | 0.2575          | 0.9      |
| 0.3216        | 21.0  | 294  | 0.2516          | 0.9227   |
| 0.3461        | 22.0  | 308  | 0.2368          | 0.9045   |
| 0.3116        | 23.0  | 322  | 0.2651          | 0.9136   |
| 0.3244        | 24.0  | 336  | 0.2820          | 0.9      |
| 0.2725        | 25.0  | 350  | 0.2320          | 0.9045   |
| 0.3377        | 26.0  | 364  | 0.2309          | 0.9318   |
| 0.2556        | 27.0  | 378  | 0.2361          | 0.9136   |
| 0.2654        | 28.0  | 392  | 0.1988          | 0.9364   |
| 0.2578        | 29.0  | 406  | 0.2322          | 0.9227   |
| 0.2262        | 30.0  | 420  | 0.1686          | 0.9409   |
| 0.2298        | 31.0  | 434  | 0.2148          | 0.9091   |
| 0.2259        | 32.0  | 448  | 0.1982          | 0.9318   |
| 0.2155        | 33.0  | 462  | 0.2340          | 0.9227   |
| 0.213         | 34.0  | 476  | 0.1359          | 0.9545   |
| 0.1812        | 35.0  | 490  | 0.1522          | 0.9409   |
| 0.1793        | 36.0  | 504  | 0.1553          | 0.9409   |
| 0.2391        | 37.0  | 518  | 0.1149          | 0.9636   |
| 0.1755        | 38.0  | 532  | 0.1627          | 0.9273   |
| 0.1907        | 39.0  | 546  | 0.1555          | 0.95     |
| 0.1814        | 40.0  | 560  | 0.1832          | 0.9409   |
| 0.1879        | 41.0  | 574  | 0.2046          | 0.9318   |
| 0.1953        | 42.0  | 588  | 0.1722          | 0.9364   |
| 0.1814        | 43.0  | 602  | 0.2270          | 0.9455   |
| 0.1932        | 44.0  | 616  | 0.1651          | 0.9318   |
| 0.1813        | 45.0  | 630  | 0.1752          | 0.9318   |
| 0.1691        | 46.0  | 644  | 0.1681          | 0.9636   |
| 0.1396        | 47.0  | 658  | 0.1604          | 0.9545   |
| 0.1647        | 48.0  | 672  | 0.1575          | 0.95     |
| 0.1501        | 49.0  | 686  | 0.1360          | 0.9545   |
| 0.1534        | 50.0  | 700  | 0.1706          | 0.9455   |


### Framework versions

- Transformers 4.54.1
- Pytorch 2.7.1
- Datasets 4.0.0
- Tokenizers 0.21.4