File size: 4,821 Bytes
3a1cd2c |
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-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_1x_deit_tiny_adamax_00001_fold4
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: 0.6666666666666666
---
<!-- 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_1x_deit_tiny_adamax_00001_fold4
This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8218
- Accuracy: 0.6667
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 6 | 1.3850 | 0.3333 |
| 1.4335 | 2.0 | 12 | 1.3341 | 0.3571 |
| 1.4335 | 3.0 | 18 | 1.2836 | 0.4286 |
| 1.2369 | 4.0 | 24 | 1.2256 | 0.5238 |
| 1.1106 | 5.0 | 30 | 1.1743 | 0.4762 |
| 1.1106 | 6.0 | 36 | 1.1379 | 0.5238 |
| 0.9897 | 7.0 | 42 | 1.1120 | 0.5952 |
| 0.9897 | 8.0 | 48 | 1.0871 | 0.6190 |
| 0.869 | 9.0 | 54 | 1.0617 | 0.5952 |
| 0.7919 | 10.0 | 60 | 1.0389 | 0.5952 |
| 0.7919 | 11.0 | 66 | 1.0206 | 0.5714 |
| 0.7005 | 12.0 | 72 | 1.0005 | 0.5714 |
| 0.7005 | 13.0 | 78 | 0.9876 | 0.5714 |
| 0.6273 | 14.0 | 84 | 0.9709 | 0.5952 |
| 0.5477 | 15.0 | 90 | 0.9546 | 0.5952 |
| 0.5477 | 16.0 | 96 | 0.9438 | 0.5714 |
| 0.4708 | 17.0 | 102 | 0.9277 | 0.5952 |
| 0.4708 | 18.0 | 108 | 0.9166 | 0.6190 |
| 0.4523 | 19.0 | 114 | 0.9086 | 0.6190 |
| 0.3797 | 20.0 | 120 | 0.9051 | 0.5952 |
| 0.3797 | 21.0 | 126 | 0.8956 | 0.6190 |
| 0.3458 | 22.0 | 132 | 0.8852 | 0.6190 |
| 0.3458 | 23.0 | 138 | 0.8841 | 0.6190 |
| 0.3057 | 24.0 | 144 | 0.8804 | 0.5952 |
| 0.2867 | 25.0 | 150 | 0.8683 | 0.6429 |
| 0.2867 | 26.0 | 156 | 0.8580 | 0.6667 |
| 0.2509 | 27.0 | 162 | 0.8515 | 0.6667 |
| 0.2509 | 28.0 | 168 | 0.8546 | 0.6429 |
| 0.2322 | 29.0 | 174 | 0.8500 | 0.6667 |
| 0.2064 | 30.0 | 180 | 0.8396 | 0.6667 |
| 0.2064 | 31.0 | 186 | 0.8363 | 0.6667 |
| 0.1928 | 32.0 | 192 | 0.8371 | 0.6667 |
| 0.1928 | 33.0 | 198 | 0.8332 | 0.6667 |
| 0.1767 | 34.0 | 204 | 0.8261 | 0.6667 |
| 0.1746 | 35.0 | 210 | 0.8249 | 0.6667 |
| 0.1746 | 36.0 | 216 | 0.8258 | 0.6667 |
| 0.1557 | 37.0 | 222 | 0.8248 | 0.6667 |
| 0.1557 | 38.0 | 228 | 0.8243 | 0.6667 |
| 0.1581 | 39.0 | 234 | 0.8225 | 0.6667 |
| 0.1477 | 40.0 | 240 | 0.8219 | 0.6667 |
| 0.1477 | 41.0 | 246 | 0.8217 | 0.6667 |
| 0.149 | 42.0 | 252 | 0.8218 | 0.6667 |
| 0.149 | 43.0 | 258 | 0.8218 | 0.6667 |
| 0.1403 | 44.0 | 264 | 0.8218 | 0.6667 |
| 0.146 | 45.0 | 270 | 0.8218 | 0.6667 |
| 0.146 | 46.0 | 276 | 0.8218 | 0.6667 |
| 0.1461 | 47.0 | 282 | 0.8218 | 0.6667 |
| 0.1461 | 48.0 | 288 | 0.8218 | 0.6667 |
| 0.1422 | 49.0 | 294 | 0.8218 | 0.6667 |
| 0.1494 | 50.0 | 300 | 0.8218 | 0.6667 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
|