metadata
base_model: MBZUAI/swiftformer-xs
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: swiftformer-xs-dmae-va-U-80
results: []
swiftformer-xs-dmae-va-U-80
This model is a fine-tuned version of MBZUAI/swiftformer-xs on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6494
- Accuracy: 0.8165
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: 40
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 0.9 | 7 | 1.3781 | 0.3486 |
| 1.3901 | 1.94 | 15 | 1.3538 | 0.3303 |
| 1.3561 | 2.97 | 23 | 1.3091 | 0.3761 |
| 1.2933 | 4.0 | 31 | 1.2623 | 0.4220 |
| 1.2933 | 4.9 | 38 | 1.2065 | 0.5138 |
| 1.2274 | 5.94 | 46 | 1.1353 | 0.5413 |
| 1.1686 | 6.97 | 54 | 1.0854 | 0.6147 |
| 1.097 | 8.0 | 62 | 1.0489 | 0.6330 |
| 1.097 | 8.9 | 69 | 1.0185 | 0.6606 |
| 1.0349 | 9.94 | 77 | 0.9682 | 0.6422 |
| 1.0161 | 10.97 | 85 | 0.9511 | 0.6055 |
| 0.9633 | 12.0 | 93 | 0.9009 | 0.6606 |
| 0.939 | 12.9 | 100 | 0.9055 | 0.6514 |
| 0.939 | 13.94 | 108 | 0.8781 | 0.6697 |
| 0.9036 | 14.97 | 116 | 0.8494 | 0.7248 |
| 0.8687 | 16.0 | 124 | 0.8503 | 0.6789 |
| 0.8535 | 16.9 | 131 | 0.8164 | 0.7248 |
| 0.8535 | 17.94 | 139 | 0.7883 | 0.7615 |
| 0.8306 | 18.97 | 147 | 0.7667 | 0.7615 |
| 0.8047 | 20.0 | 155 | 0.7600 | 0.7523 |
| 0.7735 | 20.9 | 162 | 0.7331 | 0.7615 |
| 0.784 | 21.94 | 170 | 0.7295 | 0.7523 |
| 0.784 | 22.97 | 178 | 0.7281 | 0.7431 |
| 0.7596 | 24.0 | 186 | 0.7045 | 0.7615 |
| 0.7609 | 24.9 | 193 | 0.6915 | 0.7706 |
| 0.7307 | 25.94 | 201 | 0.6970 | 0.8073 |
| 0.7307 | 26.97 | 209 | 0.6796 | 0.7615 |
| 0.7263 | 28.0 | 217 | 0.6615 | 0.7706 |
| 0.6933 | 28.9 | 224 | 0.6628 | 0.7798 |
| 0.6914 | 29.94 | 232 | 0.6596 | 0.8073 |
| 0.7192 | 30.97 | 240 | 0.6453 | 0.7982 |
| 0.7192 | 32.0 | 248 | 0.6569 | 0.7798 |
| 0.6956 | 32.9 | 255 | 0.6494 | 0.8165 |
| 0.7037 | 33.94 | 263 | 0.6478 | 0.8073 |
| 0.669 | 34.97 | 271 | 0.6415 | 0.7798 |
| 0.669 | 36.0 | 279 | 0.6441 | 0.7890 |
| 0.6715 | 36.13 | 280 | 0.6445 | 0.7798 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1