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resnet-152-finetuned_resnet152-adam-optimizer5e-4-autotags
This model is a fine-tuned version of microsoft/resnet-152 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.2399
- Accuracy: 0.9305
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: 0.0005
- 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 |
|---|---|---|---|---|
| 2.4009 | 0.99 | 65 | 2.1414 | 0.3971 |
| 0.9201 | 1.99 | 130 | 0.8123 | 0.7210 |
| 0.7575 | 2.99 | 195 | 0.5730 | 0.8124 |
| 0.4792 | 3.99 | 260 | 0.4166 | 0.8648 |
| 0.4253 | 4.99 | 325 | 0.3811 | 0.8810 |
| 0.3331 | 5.99 | 390 | 0.4290 | 0.8705 |
| 0.2347 | 6.99 | 455 | 0.4600 | 0.8952 |
| 0.1732 | 7.99 | 520 | 0.3018 | 0.8924 |
| 0.1777 | 8.99 | 585 | 0.4851 | 0.8914 |
| 0.1298 | 9.99 | 650 | 0.2941 | 0.92 |
| 0.1164 | 10.99 | 715 | 0.3915 | 0.9095 |
| 0.1284 | 11.99 | 780 | 0.3701 | 0.9152 |
| 0.0986 | 12.99 | 845 | 0.3416 | 0.9171 |
| 0.0944 | 13.99 | 910 | 0.3145 | 0.9210 |
| 0.0929 | 14.99 | 975 | 0.2677 | 0.9229 |
| 0.1014 | 15.99 | 1040 | 0.2745 | 0.9295 |
| 0.0971 | 16.99 | 1105 | 0.2932 | 0.9267 |
| 0.0691 | 17.99 | 1170 | 0.2174 | 0.9333 |
| 0.0557 | 18.99 | 1235 | 0.2233 | 0.9324 |
| 0.06 | 19.99 | 1300 | 0.2399 | 0.9305 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.1+cu117
- Datasets 2.11.0
- Tokenizers 0.13.2
