File size: 4,868 Bytes
b567e7a |
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_40x_deit_tiny_rms_0001_fold1
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: 0.7777777777777778
---
<!-- 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_40x_deit_tiny_rms_0001_fold1
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: 1.8879
- Accuracy: 0.7778
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.0915 | 1.0 | 215 | 0.6993 | 0.7556 |
| 0.0445 | 2.0 | 430 | 1.0894 | 0.8 |
| 0.0994 | 3.0 | 645 | 1.3749 | 0.7333 |
| 0.0599 | 4.0 | 860 | 1.2197 | 0.8222 |
| 0.123 | 5.0 | 1075 | 1.0909 | 0.7333 |
| 0.0208 | 6.0 | 1290 | 1.5815 | 0.7778 |
| 0.0152 | 7.0 | 1505 | 1.3429 | 0.7556 |
| 0.1165 | 8.0 | 1720 | 1.4059 | 0.8222 |
| 0.0038 | 9.0 | 1935 | 2.1318 | 0.6889 |
| 0.0001 | 10.0 | 2150 | 1.8677 | 0.7556 |
| 0.0 | 11.0 | 2365 | 1.9514 | 0.7556 |
| 0.0 | 12.0 | 2580 | 2.1201 | 0.7556 |
| 0.0 | 13.0 | 2795 | 2.2375 | 0.7556 |
| 0.0 | 14.0 | 3010 | 2.3713 | 0.7556 |
| 0.0 | 15.0 | 3225 | 2.4919 | 0.7556 |
| 0.0 | 16.0 | 3440 | 2.5759 | 0.7556 |
| 0.0 | 17.0 | 3655 | 2.6720 | 0.7556 |
| 0.0 | 18.0 | 3870 | 2.7211 | 0.7556 |
| 0.0 | 19.0 | 4085 | 2.7243 | 0.7778 |
| 0.0 | 20.0 | 4300 | 2.7162 | 0.7778 |
| 0.0 | 21.0 | 4515 | 2.7396 | 0.7778 |
| 0.0 | 22.0 | 4730 | 2.8636 | 0.7556 |
| 0.0 | 23.0 | 4945 | 2.7180 | 0.7778 |
| 0.0 | 24.0 | 5160 | 2.5977 | 0.7778 |
| 0.0 | 25.0 | 5375 | 2.4267 | 0.7778 |
| 0.0 | 26.0 | 5590 | 2.3791 | 0.7778 |
| 0.0 | 27.0 | 5805 | 2.3560 | 0.7778 |
| 0.0 | 28.0 | 6020 | 2.2693 | 0.7778 |
| 0.0 | 29.0 | 6235 | 2.3818 | 0.7778 |
| 0.0 | 30.0 | 6450 | 2.1093 | 0.7778 |
| 0.0 | 31.0 | 6665 | 2.1403 | 0.7778 |
| 0.0 | 32.0 | 6880 | 2.0697 | 0.7778 |
| 0.0 | 33.0 | 7095 | 2.1077 | 0.7778 |
| 0.0 | 34.0 | 7310 | 1.9838 | 0.7778 |
| 0.0 | 35.0 | 7525 | 2.0013 | 0.7778 |
| 0.0 | 36.0 | 7740 | 1.9512 | 0.7778 |
| 0.0 | 37.0 | 7955 | 1.9785 | 0.7778 |
| 0.0 | 38.0 | 8170 | 1.9833 | 0.7778 |
| 0.0 | 39.0 | 8385 | 1.9247 | 0.7778 |
| 0.0 | 40.0 | 8600 | 1.9583 | 0.7778 |
| 0.0 | 41.0 | 8815 | 1.9257 | 0.7778 |
| 0.0 | 42.0 | 9030 | 1.9718 | 0.7778 |
| 0.0 | 43.0 | 9245 | 1.9220 | 0.7778 |
| 0.0 | 44.0 | 9460 | 1.9083 | 0.7778 |
| 0.0 | 45.0 | 9675 | 1.9217 | 0.7778 |
| 0.0 | 46.0 | 9890 | 1.8800 | 0.7778 |
| 0.0 | 47.0 | 10105 | 1.8880 | 0.7778 |
| 0.0 | 48.0 | 10320 | 1.8890 | 0.7778 |
| 0.0 | 49.0 | 10535 | 1.8815 | 0.7778 |
| 0.0 | 50.0 | 10750 | 1.8879 | 0.7778 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.1.1+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2
|