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---
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: 0.9102040816326531
---
<!-- 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: 0.3980
- Accuracy: 0.9102
## 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: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.9105 | 0.98 | 30 | 3.7931 | 0.0551 |
| 3.2821 | 1.98 | 61 | 2.9878 | 0.2755 |
| 2.4752 | 2.99 | 92 | 2.1760 | 0.4408 |
| 1.9958 | 4.0 | 123 | 1.6964 | 0.5327 |
| 1.6609 | 4.98 | 153 | 1.4001 | 0.6265 |
| 1.4328 | 5.98 | 184 | 1.1766 | 0.6796 |
| 1.2677 | 6.99 | 215 | 1.0262 | 0.7163 |
| 1.1174 | 8.0 | 246 | 0.8758 | 0.7653 |
| 1.0564 | 8.98 | 276 | 0.7675 | 0.8184 |
| 0.9003 | 9.98 | 307 | 0.7161 | 0.8286 |
| 0.8711 | 10.99 | 338 | 0.6461 | 0.8224 |
| 0.7954 | 12.0 | 369 | 0.5683 | 0.8653 |
| 0.743 | 12.98 | 399 | 0.5438 | 0.8510 |
| 0.6914 | 13.98 | 430 | 0.5129 | 0.8878 |
| 0.6714 | 14.99 | 461 | 0.4418 | 0.8857 |
| 0.663 | 16.0 | 492 | 0.4555 | 0.8694 |
| 0.6326 | 16.98 | 522 | 0.4746 | 0.8755 |
| 0.5831 | 17.98 | 553 | 0.4263 | 0.8776 |
| 0.571 | 18.99 | 584 | 0.4305 | 0.8857 |
| 0.6543 | 19.51 | 600 | 0.3980 | 0.9102 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.0.0
- Datasets 2.12.0
- Tokenizers 0.14.1
|