metadata
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: 0.7810232220609579
font-identifier
This model is a fine-tuned version of microsoft/resnet-18 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.8935
- Accuracy: 0.7810
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: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 7.2836 | 1.0 | 344 | 7.2178 | 0.0038 |
| 6.6696 | 2.0 | 689 | 6.4685 | 0.0408 |
| 5.85 | 3.0 | 1034 | 5.3897 | 0.1254 |
| 5.0457 | 4.0 | 1379 | 4.4771 | 0.2143 |
| 4.3784 | 5.0 | 1723 | 3.6429 | 0.3242 |
| 3.809 | 6.0 | 2068 | 3.1236 | 0.4031 |
| 3.4229 | 7.0 | 2413 | 2.6388 | 0.4672 |
| 2.8977 | 8.0 | 2758 | 2.3279 | 0.5102 |
| 2.78 | 9.0 | 3102 | 2.0974 | 0.5682 |
| 2.4452 | 10.0 | 3447 | 1.8605 | 0.6027 |
| 2.2195 | 11.0 | 3792 | 1.6783 | 0.6312 |
| 2.1097 | 12.0 | 4137 | 1.6049 | 0.6390 |
| 1.9025 | 13.0 | 4481 | 1.4255 | 0.6912 |
| 1.7973 | 14.0 | 4826 | 1.3253 | 0.7075 |
| 1.7647 | 15.0 | 5171 | 1.3030 | 0.7032 |
| 1.6772 | 16.0 | 5516 | 1.1988 | 0.7210 |
| 1.5523 | 17.0 | 5860 | 1.1040 | 0.7395 |
| 1.4821 | 18.0 | 6205 | 1.0786 | 0.7380 |
| 1.3764 | 19.0 | 6550 | 1.0603 | 0.7471 |
| 1.2913 | 20.0 | 6895 | 1.0169 | 0.7542 |
| 1.3479 | 21.0 | 7239 | 0.9999 | 0.7563 |
| 1.3133 | 22.0 | 7584 | 0.9928 | 0.7594 |
| 1.2241 | 23.0 | 7929 | 0.9342 | 0.7649 |
| 1.1651 | 24.0 | 8274 | 0.9283 | 0.7658 |
| 1.1605 | 25.0 | 8618 | 0.9176 | 0.7720 |
| 1.0283 | 26.0 | 8963 | 0.8970 | 0.7767 |
| 1.1211 | 27.0 | 9308 | 0.8983 | 0.7754 |
| 1.1563 | 28.0 | 9653 | 0.8729 | 0.7801 |
| 1.1399 | 29.0 | 9997 | 0.9021 | 0.7732 |
| 1.1715 | 29.93 | 10320 | 0.8935 | 0.7810 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.0.0
- Datasets 2.15.0
- Tokenizers 0.15.0