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models
This model is a fine-tuned version of microsoft/resnet-18 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4704
- Accuracy: 0.8182
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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- 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 |
|---|---|---|---|---|
| 1.4144 | 0.99 | 20 | 0.9938 | 0.7 |
| 0.7896 | 1.98 | 40 | 0.7022 | 0.7152 |
| 0.6191 | 2.96 | 60 | 0.6079 | 0.7636 |
| 0.6114 | 4.0 | 81 | 0.5554 | 0.7939 |
| 0.5365 | 4.99 | 101 | 0.5233 | 0.8152 |
| 0.4989 | 5.98 | 121 | 0.4934 | 0.8303 |
| 0.5111 | 6.96 | 141 | 0.5181 | 0.8 |
| 0.476 | 8.0 | 162 | 0.4844 | 0.8182 |
| 0.4655 | 8.99 | 182 | 0.4870 | 0.8152 |
| 0.4335 | 9.98 | 202 | 0.4802 | 0.8242 |
| 0.44 | 10.96 | 222 | 0.4776 | 0.8182 |
| 0.3989 | 12.0 | 243 | 0.4804 | 0.8182 |
| 0.4007 | 12.99 | 263 | 0.4768 | 0.8242 |
| 0.3987 | 13.98 | 283 | 0.4610 | 0.8303 |
| 0.3922 | 14.96 | 303 | 0.4578 | 0.8212 |
| 0.3924 | 16.0 | 324 | 0.4804 | 0.8182 |
| 0.3995 | 16.99 | 344 | 0.4736 | 0.8121 |
| 0.3623 | 17.98 | 364 | 0.4715 | 0.8121 |
| 0.3621 | 18.96 | 384 | 0.4671 | 0.8212 |
| 0.3629 | 19.75 | 400 | 0.4704 | 0.8182 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.0
- Tokenizers 0.13.3
