---
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: 0.9162162162162162
---

<!-- 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:
- Accuracy: 0.9162
- Loss: 0.2760

## 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 OptimizerNames.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 | Accuracy | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| 3.7676        | 1.0   | 24   | 0.0459   | 3.6832          |
| 3.607         | 2.0   | 48   | 0.0919   | 3.4400          |
| 3.2234        | 3.0   | 72   | 0.1919   | 3.0452          |
| 2.8944        | 4.0   | 96   | 0.3324   | 2.5182          |
| 2.1637        | 5.0   | 120  | 0.4351   | 2.0193          |
| 1.9347        | 6.0   | 144  | 0.5595   | 1.6222          |
| 1.6851        | 7.0   | 168  | 0.6297   | 1.3065          |
| 1.369         | 8.0   | 192  | 0.6919   | 1.0945          |
| 1.2987        | 9.0   | 216  | 0.7270   | 0.9188          |
| 1.1044        | 10.0  | 240  | 0.7541   | 0.8216          |
| 1.044         | 11.0  | 264  | 0.8      | 0.7295          |
| 1.0134        | 12.0  | 288  | 0.8270   | 0.6655          |
| 0.9284        | 13.0  | 312  | 0.8189   | 0.6212          |
| 0.8603        | 14.0  | 336  | 0.8216   | 0.5687          |
| 0.7748        | 15.0  | 360  | 0.8649   | 0.5291          |
| 0.8133        | 16.0  | 384  | 0.8324   | 0.5337          |
| 0.8379        | 17.0  | 408  | 0.8486   | 0.4993          |
| 0.751         | 18.0  | 432  | 0.8514   | 0.4632          |
| 0.8585        | 19.0  | 456  | 0.8162   | 0.4908          |
| 0.6627        | 20.0  | 480  | 0.8622   | 0.4358          |
| 0.6497        | 21.0  | 504  | 0.8486   | 0.4240          |
| 0.6422        | 22.0  | 528  | 0.8486   | 0.4143          |
| 0.5964        | 23.0  | 552  | 0.8676   | 0.3912          |
| 0.5793        | 24.0  | 576  | 0.8568   | 0.4026          |
| 0.5909        | 25.0  | 600  | 0.8838   | 0.3531          |
| 0.593         | 26.0  | 624  | 0.8811   | 0.3661          |
| 0.5957        | 27.0  | 648  | 0.8892   | 0.3674          |
| 0.5869        | 28.0  | 672  | 0.8892   | 0.3710          |
| 0.4999        | 29.0  | 696  | 0.8919   | 0.3422          |
| 0.4843        | 30.0  | 720  | 0.8946   | 0.3178          |
| 0.5352        | 31.0  | 744  | 0.8865   | 0.3129          |
| 0.4937        | 32.0  | 768  | 0.8973   | 0.3399          |
| 0.483         | 33.0  | 792  | 0.8973   | 0.2855          |
| 0.4265        | 34.0  | 816  | 0.9      | 0.3316          |
| 0.4412        | 35.0  | 840  | 0.8865   | 0.3273          |
| 0.4324        | 36.0  | 864  | 0.8973   | 0.3167          |
| 0.4681        | 37.0  | 888  | 0.9270   | 0.2944          |
| 0.4813        | 38.0  | 912  | 0.9135   | 0.2943          |
| 0.4585        | 39.0  | 936  | 0.9027   | 0.3019          |
| 0.4151        | 40.0  | 960  | 0.8892   | 0.3399          |
| 0.4351        | 41.0  | 984  | 0.9081   | 0.2623          |
| 0.4364        | 42.0  | 1008 | 0.9135   | 0.2892          |
| 0.4632        | 43.0  | 1032 | 0.9081   | 0.3086          |
| 0.3867        | 44.0  | 1056 | 0.9      | 0.2913          |
| 0.4007        | 45.0  | 1080 | 0.9135   | 0.2502          |
| 0.3848        | 46.0  | 1104 | 0.9162   | 0.2702          |
| 0.4061        | 47.0  | 1128 | 0.9162   | 0.2634          |
| 0.3901        | 48.0  | 1152 | 0.9054   | 0.2975          |
| 0.3794        | 49.0  | 1176 | 0.8973   | 0.2590          |
| 0.3583        | 50.0  | 1200 | 0.9162   | 0.2760          |


### Framework versions

- Transformers 4.53.3
- Pytorch 2.7.1
- Datasets 4.0.0
- Tokenizers 0.21.4