File size: 4,869 Bytes
f887a4e |
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: smids_3x_deit_small_sgd_0001_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: 0.7820299500831946
---
<!-- 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. -->
# smids_3x_deit_small_sgd_0001_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: 0.5927
- Accuracy: 0.7820
## 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: 0.0001
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.0529 | 1.0 | 225 | 1.0464 | 0.4542 |
| 1.0393 | 2.0 | 450 | 1.0215 | 0.4759 |
| 1.0194 | 3.0 | 675 | 0.9971 | 0.5158 |
| 0.9608 | 4.0 | 900 | 0.9729 | 0.5541 |
| 0.9743 | 5.0 | 1125 | 0.9487 | 0.6023 |
| 0.9002 | 6.0 | 1350 | 0.9258 | 0.6206 |
| 0.8961 | 7.0 | 1575 | 0.9030 | 0.6373 |
| 0.9282 | 8.0 | 1800 | 0.8813 | 0.6539 |
| 0.856 | 9.0 | 2025 | 0.8605 | 0.6705 |
| 0.8441 | 10.0 | 2250 | 0.8407 | 0.6772 |
| 0.8723 | 11.0 | 2475 | 0.8225 | 0.6839 |
| 0.7789 | 12.0 | 2700 | 0.8048 | 0.6955 |
| 0.7952 | 13.0 | 2925 | 0.7885 | 0.7055 |
| 0.7937 | 14.0 | 3150 | 0.7729 | 0.7155 |
| 0.8007 | 15.0 | 3375 | 0.7585 | 0.7255 |
| 0.769 | 16.0 | 3600 | 0.7449 | 0.7238 |
| 0.7262 | 17.0 | 3825 | 0.7325 | 0.7255 |
| 0.7259 | 18.0 | 4050 | 0.7208 | 0.7238 |
| 0.7176 | 19.0 | 4275 | 0.7099 | 0.7255 |
| 0.6791 | 20.0 | 4500 | 0.6998 | 0.7271 |
| 0.7106 | 21.0 | 4725 | 0.6905 | 0.7338 |
| 0.6951 | 22.0 | 4950 | 0.6819 | 0.7371 |
| 0.7193 | 23.0 | 5175 | 0.6739 | 0.7471 |
| 0.6759 | 24.0 | 5400 | 0.6663 | 0.7521 |
| 0.6975 | 25.0 | 5625 | 0.6593 | 0.7537 |
| 0.6391 | 26.0 | 5850 | 0.6529 | 0.7571 |
| 0.6617 | 27.0 | 6075 | 0.6469 | 0.7604 |
| 0.6434 | 28.0 | 6300 | 0.6413 | 0.7604 |
| 0.6619 | 29.0 | 6525 | 0.6362 | 0.7587 |
| 0.6444 | 30.0 | 6750 | 0.6315 | 0.7571 |
| 0.6161 | 31.0 | 6975 | 0.6270 | 0.7604 |
| 0.6193 | 32.0 | 7200 | 0.6230 | 0.7671 |
| 0.5926 | 33.0 | 7425 | 0.6193 | 0.7654 |
| 0.5861 | 34.0 | 7650 | 0.6159 | 0.7754 |
| 0.6256 | 35.0 | 7875 | 0.6127 | 0.7770 |
| 0.6099 | 36.0 | 8100 | 0.6099 | 0.7754 |
| 0.5932 | 37.0 | 8325 | 0.6073 | 0.7770 |
| 0.5988 | 38.0 | 8550 | 0.6049 | 0.7804 |
| 0.574 | 39.0 | 8775 | 0.6028 | 0.7787 |
| 0.5835 | 40.0 | 9000 | 0.6009 | 0.7787 |
| 0.5292 | 41.0 | 9225 | 0.5992 | 0.7787 |
| 0.586 | 42.0 | 9450 | 0.5977 | 0.7804 |
| 0.5537 | 43.0 | 9675 | 0.5964 | 0.7820 |
| 0.5573 | 44.0 | 9900 | 0.5953 | 0.7837 |
| 0.5715 | 45.0 | 10125 | 0.5945 | 0.7820 |
| 0.6072 | 46.0 | 10350 | 0.5938 | 0.7820 |
| 0.5714 | 47.0 | 10575 | 0.5933 | 0.7837 |
| 0.5684 | 48.0 | 10800 | 0.5929 | 0.7820 |
| 0.5949 | 49.0 | 11025 | 0.5927 | 0.7820 |
| 0.5423 | 50.0 | 11250 | 0.5927 | 0.7820 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2
|