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Train
This model is a fine-tuned version of microsoft/resnet-101 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.8647
- Accuracy: 0.3282
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: 0.0002
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.8186 | 0.13 | 100 | 2.8698 | 0.3205 |
| 3.3401 | 0.26 | 200 | 2.8968 | 0.3026 |
| 2.8737 | 0.39 | 300 | 2.8947 | 0.3128 |
| 3.1365 | 0.51 | 400 | 2.8635 | 0.3256 |
| 2.9823 | 0.64 | 500 | 2.8724 | 0.3128 |
| 2.7439 | 0.77 | 600 | 2.8736 | 0.3333 |
| 2.7354 | 0.9 | 700 | 2.8708 | 0.3436 |
| 2.688 | 1.03 | 800 | 2.8709 | 0.3231 |
| 3.172 | 1.16 | 900 | 2.9082 | 0.2692 |
| 2.7289 | 1.29 | 1000 | 2.8873 | 0.3564 |
| 2.7369 | 1.41 | 1100 | 2.9032 | 0.3 |
| 2.879 | 1.54 | 1200 | 2.8807 | 0.3308 |
| 2.9532 | 1.67 | 1300 | 2.8706 | 0.2923 |
| 3.2004 | 1.8 | 1400 | 2.8598 | 0.2872 |
| 2.9607 | 1.93 | 1500 | 2.8647 | 0.3282 |
Framework versions
- Transformers 4.30.1
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
