File size: 4,826 Bytes
befb434 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 |
---
license: apache-2.0
base_model: facebook/deit-small-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_5x_deit_small_adamax_00001_fold2
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: test
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.6888888888888889
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# hushem_5x_deit_small_adamax_00001_fold2
This model is a fine-tuned version of [facebook/deit-small-patch16-224](https://huggingface.co/facebook/deit-small-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4402
- Accuracy: 0.6889
## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2515 | 1.0 | 27 | 1.2615 | 0.5333 |
| 0.9391 | 2.0 | 54 | 1.2122 | 0.5556 |
| 0.6766 | 3.0 | 81 | 1.1537 | 0.5333 |
| 0.5382 | 4.0 | 108 | 1.1591 | 0.6 |
| 0.3747 | 5.0 | 135 | 1.0974 | 0.6444 |
| 0.2681 | 6.0 | 162 | 1.0815 | 0.6444 |
| 0.1892 | 7.0 | 189 | 1.1005 | 0.6222 |
| 0.1214 | 8.0 | 216 | 1.0974 | 0.6222 |
| 0.0863 | 9.0 | 243 | 1.0922 | 0.6444 |
| 0.0475 | 10.0 | 270 | 1.1018 | 0.6667 |
| 0.0299 | 11.0 | 297 | 1.1054 | 0.6889 |
| 0.0156 | 12.0 | 324 | 1.1555 | 0.6667 |
| 0.0095 | 13.0 | 351 | 1.1847 | 0.6667 |
| 0.0067 | 14.0 | 378 | 1.2033 | 0.6667 |
| 0.0051 | 15.0 | 405 | 1.2483 | 0.6667 |
| 0.004 | 16.0 | 432 | 1.2613 | 0.6667 |
| 0.0032 | 17.0 | 459 | 1.2726 | 0.6667 |
| 0.0028 | 18.0 | 486 | 1.2843 | 0.6667 |
| 0.0026 | 19.0 | 513 | 1.2998 | 0.6667 |
| 0.0021 | 20.0 | 540 | 1.3093 | 0.6667 |
| 0.0019 | 21.0 | 567 | 1.3233 | 0.6667 |
| 0.0018 | 22.0 | 594 | 1.3315 | 0.6667 |
| 0.0015 | 23.0 | 621 | 1.3379 | 0.6667 |
| 0.0014 | 24.0 | 648 | 1.3489 | 0.6667 |
| 0.0014 | 25.0 | 675 | 1.3547 | 0.6667 |
| 0.0013 | 26.0 | 702 | 1.3608 | 0.6889 |
| 0.0012 | 27.0 | 729 | 1.3706 | 0.6667 |
| 0.0011 | 28.0 | 756 | 1.3780 | 0.6667 |
| 0.0012 | 29.0 | 783 | 1.3808 | 0.6889 |
| 0.0011 | 30.0 | 810 | 1.3868 | 0.6889 |
| 0.001 | 31.0 | 837 | 1.3922 | 0.6889 |
| 0.001 | 32.0 | 864 | 1.3991 | 0.6889 |
| 0.0009 | 33.0 | 891 | 1.4019 | 0.6889 |
| 0.0009 | 34.0 | 918 | 1.4078 | 0.6889 |
| 0.0009 | 35.0 | 945 | 1.4120 | 0.6889 |
| 0.0008 | 36.0 | 972 | 1.4161 | 0.6889 |
| 0.0008 | 37.0 | 999 | 1.4179 | 0.6889 |
| 0.0008 | 38.0 | 1026 | 1.4222 | 0.6889 |
| 0.0007 | 39.0 | 1053 | 1.4264 | 0.6889 |
| 0.0007 | 40.0 | 1080 | 1.4282 | 0.6889 |
| 0.0007 | 41.0 | 1107 | 1.4320 | 0.6889 |
| 0.0007 | 42.0 | 1134 | 1.4342 | 0.6889 |
| 0.0007 | 43.0 | 1161 | 1.4365 | 0.6889 |
| 0.0007 | 44.0 | 1188 | 1.4366 | 0.6889 |
| 0.0007 | 45.0 | 1215 | 1.4383 | 0.6889 |
| 0.0007 | 46.0 | 1242 | 1.4394 | 0.6889 |
| 0.0007 | 47.0 | 1269 | 1.4399 | 0.6889 |
| 0.0007 | 48.0 | 1296 | 1.4402 | 0.6889 |
| 0.0007 | 49.0 | 1323 | 1.4402 | 0.6889 |
| 0.0007 | 50.0 | 1350 | 1.4402 | 0.6889 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
|