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# 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: 0.0010
- Accuracy: 1.0

## 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: 50

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 3.2404        | 0.9524  | 15   | 3.1135          | 0.06     |
| 2.7846        | 1.9683  | 31   | 2.4576          | 0.33     |
| 2.3956        | 2.9841  | 47   | 1.7152          | 0.58     |
| 1.6171        | 4.0     | 63   | 1.0931          | 0.775    |
| 1.2882        | 4.9524  | 78   | 0.6347          | 0.85     |
| 0.7191        | 5.9683  | 94   | 0.3957          | 0.94     |
| 0.5196        | 6.9841  | 110  | 0.2080          | 0.965    |
| 0.3999        | 8.0     | 126  | 0.1480          | 0.965    |
| 0.2476        | 8.9524  | 141  | 0.0934          | 0.985    |
| 0.2176        | 9.9683  | 157  | 0.0768          | 0.99     |
| 0.194         | 10.9841 | 173  | 0.0365          | 0.995    |
| 0.1572        | 12.0    | 189  | 0.0616          | 0.985    |
| 0.1381        | 12.9524 | 204  | 0.0640          | 0.985    |
| 0.1291        | 13.9683 | 220  | 0.0522          | 0.985    |
| 0.094         | 14.9841 | 236  | 0.0442          | 0.99     |
| 0.1037        | 16.0    | 252  | 0.0492          | 0.99     |
| 0.1067        | 16.9524 | 267  | 0.0629          | 0.985    |
| 0.0912        | 17.9683 | 283  | 0.0486          | 0.985    |
| 0.0702        | 18.9841 | 299  | 0.0344          | 0.99     |
| 0.0677        | 20.0    | 315  | 0.0242          | 0.995    |
| 0.0566        | 20.9524 | 330  | 0.0295          | 0.99     |
| 0.0742        | 21.9683 | 346  | 0.0300          | 0.99     |
| 0.0675        | 22.9841 | 362  | 0.0159          | 1.0      |
| 0.0501        | 24.0    | 378  | 0.0105          | 0.995    |
| 0.0651        | 24.9524 | 393  | 0.0362          | 0.995    |
| 0.0665        | 25.9683 | 409  | 0.0335          | 0.985    |
| 0.0533        | 26.9841 | 425  | 0.0369          | 0.99     |
| 0.0487        | 28.0    | 441  | 0.0296          | 0.99     |
| 0.0384        | 28.9524 | 456  | 0.0177          | 0.995    |
| 0.038         | 29.9683 | 472  | 0.0176          | 0.995    |
| 0.0342        | 30.9841 | 488  | 0.0165          | 0.995    |
| 0.055         | 32.0    | 504  | 0.0199          | 0.995    |
| 0.0418        | 32.9524 | 519  | 0.0022          | 1.0      |
| 0.0447        | 33.9683 | 535  | 0.0071          | 0.995    |
| 0.0436        | 34.9841 | 551  | 0.0587          | 0.98     |
| 0.0307        | 36.0    | 567  | 0.0244          | 0.995    |
| 0.0413        | 36.9524 | 582  | 0.0227          | 0.99     |
| 0.0351        | 37.9683 | 598  | 0.0323          | 0.99     |
| 0.0267        | 38.9841 | 614  | 0.0510          | 0.985    |
| 0.0259        | 40.0    | 630  | 0.0009          | 1.0      |
| 0.0245        | 40.9524 | 645  | 0.0017          | 1.0      |
| 0.0227        | 41.9683 | 661  | 0.0208          | 0.995    |
| 0.0458        | 42.9841 | 677  | 0.0445          | 0.99     |
| 0.0263        | 44.0    | 693  | 0.0339          | 0.99     |
| 0.0458        | 44.9524 | 708  | 0.0124          | 0.995    |
| 0.0374        | 45.9683 | 724  | 0.0253          | 0.995    |
| 0.0413        | 46.9841 | 740  | 0.0025          | 1.0      |
| 0.0413        | 47.6190 | 750  | 0.0010          | 1.0      |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.5.0
- Datasets 3.1.0
- Tokenizers 0.20.1

abeezee aclonica baloo2 bangers barlowcondensed deftonestylus kanit onean worksans dintalksans kingsbridgeexlt steelfishoutline adamina adventpro akronim aladin alef aleo alexbrush amaranth