---
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: 0.963265306122449
---

<!-- 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: 0.1172
- Accuracy: 0.9633

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 4.0243        | 0.98  | 30   | 3.9884          | 0.0204   |
| 3.7051        | 1.98  | 61   | 3.6012          | 0.0776   |
| 3.2036        | 2.99  | 92   | 2.9556          | 0.2939   |
| 2.6413        | 4.0   | 123  | 2.3054          | 0.4531   |
| 2.1015        | 4.98  | 153  | 1.7366          | 0.5224   |
| 1.6508        | 5.98  | 184  | 1.3509          | 0.6367   |
| 1.3986        | 6.99  | 215  | 1.0938          | 0.7163   |
| 1.1918        | 8.0   | 246  | 0.9012          | 0.7735   |
| 1.0633        | 8.98  | 276  | 0.7464          | 0.8143   |
| 0.8771        | 9.98  | 307  | 0.6569          | 0.8306   |
| 0.8309        | 10.99 | 338  | 0.5536          | 0.8551   |
| 0.7093        | 12.0  | 369  | 0.4795          | 0.8796   |
| 0.6579        | 12.98 | 399  | 0.4176          | 0.8837   |
| 0.5827        | 13.98 | 430  | 0.3888          | 0.8980   |
| 0.5418        | 14.99 | 461  | 0.3255          | 0.9122   |
| 0.5102        | 16.0  | 492  | 0.3139          | 0.9265   |
| 0.472         | 16.98 | 522  | 0.3141          | 0.9163   |
| 0.4273        | 17.98 | 553  | 0.2673          | 0.9245   |
| 0.384         | 18.99 | 584  | 0.2487          | 0.9265   |
| 0.3917        | 20.0  | 615  | 0.2353          | 0.9388   |
| 0.418         | 20.98 | 645  | 0.2113          | 0.9490   |
| 0.3662        | 21.98 | 676  | 0.2095          | 0.9327   |
| 0.3258        | 22.99 | 707  | 0.2139          | 0.9429   |
| 0.3268        | 24.0  | 738  | 0.1962          | 0.9449   |
| 0.3048        | 24.98 | 768  | 0.1935          | 0.9408   |
| 0.2696        | 25.98 | 799  | 0.2112          | 0.9408   |
| 0.2524        | 26.99 | 830  | 0.2310          | 0.9306   |
| 0.2491        | 28.0  | 861  | 0.1827          | 0.9449   |
| 0.2542        | 28.98 | 891  | 0.1720          | 0.9592   |
| 0.2898        | 29.98 | 922  | 0.1605          | 0.9490   |
| 0.2298        | 30.99 | 953  | 0.1326          | 0.9633   |
| 0.2137        | 32.0  | 984  | 0.1438          | 0.9571   |
| 0.2002        | 32.98 | 1014 | 0.1379          | 0.9551   |
| 0.2013        | 33.98 | 1045 | 0.1261          | 0.9653   |
| 0.1862        | 34.99 | 1076 | 0.1674          | 0.9408   |
| 0.1993        | 36.0  | 1107 | 0.1423          | 0.9571   |
| 0.2063        | 36.98 | 1137 | 0.1406          | 0.9592   |
| 0.2088        | 37.98 | 1168 | 0.1717          | 0.9429   |
| 0.1711        | 38.99 | 1199 | 0.1539          | 0.9510   |
| 0.1804        | 40.0  | 1230 | 0.1421          | 0.9571   |
| 0.1793        | 40.98 | 1260 | 0.0765          | 0.9776   |
| 0.2139        | 41.98 | 1291 | 0.1859          | 0.9449   |
| 0.1678        | 42.99 | 1322 | 0.1067          | 0.9796   |
| 0.1675        | 44.0  | 1353 | 0.0985          | 0.9735   |
| 0.1681        | 44.98 | 1383 | 0.1093          | 0.9653   |
| 0.1625        | 45.98 | 1414 | 0.1402          | 0.9592   |
| 0.1987        | 46.99 | 1445 | 0.1250          | 0.9673   |
| 0.1728        | 48.0  | 1476 | 0.1293          | 0.9633   |
| 0.1337        | 48.78 | 1500 | 0.1172          | 0.9633   |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.0.0
- Datasets 2.12.0
- Tokenizers 0.14.1