metadata
base_model: MBZUAI/swiftformer-xs
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: swiftformer-xs-dmae-va-U5-42
results: []
swiftformer-xs-dmae-va-U5-42
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: 1.0447
- Accuracy: 0.55
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: 42
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 0.9 | 7 | 1.3144 | 0.4833 |
| 1.3947 | 1.94 | 15 | 1.3154 | 0.4 |
| 1.3947 | 2.97 | 23 | 1.2849 | 0.4167 |
| 1.3608 | 4.0 | 31 | 1.2512 | 0.4667 |
| 1.3048 | 4.9 | 38 | 1.2340 | 0.55 |
| 1.3048 | 5.94 | 46 | 1.2118 | 0.5833 |
| 1.2456 | 6.97 | 54 | 1.2077 | 0.55 |
| 1.186 | 8.0 | 62 | 1.1672 | 0.5333 |
| 1.186 | 8.9 | 69 | 1.1565 | 0.6167 |
| 1.1218 | 9.94 | 77 | 1.1532 | 0.5833 |
| 1.0731 | 10.97 | 85 | 1.1304 | 0.5833 |
| 1.0731 | 12.0 | 93 | 1.1664 | 0.5167 |
| 1.0135 | 12.9 | 100 | 1.1222 | 0.55 |
| 0.9783 | 13.94 | 108 | 1.1404 | 0.5333 |
| 0.9783 | 14.97 | 116 | 1.1022 | 0.5833 |
| 0.9195 | 16.0 | 124 | 1.0996 | 0.55 |
| 0.9195 | 16.9 | 131 | 1.0715 | 0.6 |
| 0.9023 | 17.94 | 139 | 1.0779 | 0.5833 |
| 0.8575 | 18.97 | 147 | 1.0797 | 0.5667 |
| 0.8575 | 20.0 | 155 | 1.0508 | 0.5833 |
| 0.8519 | 20.9 | 162 | 1.0500 | 0.5833 |
| 0.8098 | 21.94 | 170 | 1.0212 | 0.5667 |
| 0.8098 | 22.97 | 178 | 1.0041 | 0.5833 |
| 0.8018 | 24.0 | 186 | 1.0197 | 0.5667 |
| 0.7709 | 24.9 | 193 | 1.0283 | 0.5333 |
| 0.7709 | 25.94 | 201 | 1.0303 | 0.55 |
| 0.7642 | 26.97 | 209 | 1.0100 | 0.5833 |
| 0.7322 | 28.0 | 217 | 1.0475 | 0.5333 |
| 0.7322 | 28.9 | 224 | 1.0667 | 0.55 |
| 0.7245 | 29.94 | 232 | 1.0743 | 0.55 |
| 0.7254 | 30.97 | 240 | 1.0416 | 0.5333 |
| 0.7254 | 32.0 | 248 | 1.0664 | 0.5667 |
| 0.7201 | 32.9 | 255 | 1.0393 | 0.55 |
| 0.7201 | 33.94 | 263 | 1.0284 | 0.55 |
| 0.6968 | 34.97 | 271 | 1.0420 | 0.55 |
| 0.7073 | 36.0 | 279 | 1.0396 | 0.5333 |
| 0.7073 | 36.9 | 286 | 1.0640 | 0.55 |
| 0.6891 | 37.94 | 294 | 1.0447 | 0.55 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2