vit-msn-small-finetuned-galaxy10-decals
This model is a fine-tuned version of facebook/vit-msn-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3987
- Accuracy: 0.8729
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.9097 | 0.9978 | 112 | 0.7858 | 0.7295 |
| 0.8257 | 1.9955 | 224 | 0.5902 | 0.7940 |
| 0.6911 | 2.9933 | 336 | 0.5490 | 0.8178 |
| 0.6293 | 4.0 | 449 | 0.5251 | 0.8184 |
| 0.555 | 4.9978 | 561 | 0.5009 | 0.8341 |
| 0.5486 | 5.9955 | 673 | 0.5087 | 0.8259 |
| 0.5012 | 6.9933 | 785 | 0.4373 | 0.8566 |
| 0.4853 | 8.0 | 898 | 0.4146 | 0.8679 |
| 0.4049 | 8.9978 | 1010 | 0.3987 | 0.8729 |
| 0.4463 | 9.9777 | 1120 | 0.3896 | 0.8710 |
Framework versions
- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1