File size: 4,873 Bytes
b389d9e |
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: microsoft/beit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: smids_3x_beit_base_adamax_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: 0.9115191986644408
---
<!-- 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_beit_base_adamax_0001_fold1
This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7494
- Accuracy: 0.9115
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.3678 | 1.0 | 226 | 0.3292 | 0.8614 |
| 0.2124 | 2.0 | 452 | 0.3720 | 0.8815 |
| 0.1134 | 3.0 | 678 | 0.4692 | 0.8631 |
| 0.0789 | 4.0 | 904 | 0.3549 | 0.9032 |
| 0.0454 | 5.0 | 1130 | 0.4305 | 0.9048 |
| 0.0205 | 6.0 | 1356 | 0.5024 | 0.9149 |
| 0.001 | 7.0 | 1582 | 0.5548 | 0.9065 |
| 0.0104 | 8.0 | 1808 | 0.5394 | 0.8998 |
| 0.0382 | 9.0 | 2034 | 0.5732 | 0.9149 |
| 0.0007 | 10.0 | 2260 | 0.6012 | 0.9098 |
| 0.0391 | 11.0 | 2486 | 0.5763 | 0.9082 |
| 0.0059 | 12.0 | 2712 | 0.6108 | 0.9065 |
| 0.0173 | 13.0 | 2938 | 0.5672 | 0.9115 |
| 0.017 | 14.0 | 3164 | 0.7490 | 0.8982 |
| 0.011 | 15.0 | 3390 | 0.6808 | 0.9065 |
| 0.0001 | 16.0 | 3616 | 0.6376 | 0.9115 |
| 0.01 | 17.0 | 3842 | 0.6232 | 0.9065 |
| 0.001 | 18.0 | 4068 | 0.6761 | 0.8982 |
| 0.0042 | 19.0 | 4294 | 0.7354 | 0.9115 |
| 0.0001 | 20.0 | 4520 | 0.6861 | 0.9098 |
| 0.0007 | 21.0 | 4746 | 0.7202 | 0.9065 |
| 0.0044 | 22.0 | 4972 | 0.6969 | 0.9082 |
| 0.0048 | 23.0 | 5198 | 0.6620 | 0.9199 |
| 0.0 | 24.0 | 5424 | 0.7820 | 0.8998 |
| 0.0 | 25.0 | 5650 | 0.6630 | 0.9149 |
| 0.0 | 26.0 | 5876 | 0.6962 | 0.9165 |
| 0.0 | 27.0 | 6102 | 0.7046 | 0.9149 |
| 0.0119 | 28.0 | 6328 | 0.8033 | 0.9032 |
| 0.0 | 29.0 | 6554 | 0.6906 | 0.9115 |
| 0.0002 | 30.0 | 6780 | 0.6827 | 0.9098 |
| 0.0002 | 31.0 | 7006 | 0.7730 | 0.9065 |
| 0.0 | 32.0 | 7232 | 0.8017 | 0.9015 |
| 0.004 | 33.0 | 7458 | 0.7703 | 0.9098 |
| 0.0001 | 34.0 | 7684 | 0.7283 | 0.9098 |
| 0.0 | 35.0 | 7910 | 0.7503 | 0.9065 |
| 0.0 | 36.0 | 8136 | 0.7083 | 0.9149 |
| 0.0 | 37.0 | 8362 | 0.7770 | 0.9048 |
| 0.0 | 38.0 | 8588 | 0.7053 | 0.9165 |
| 0.0 | 39.0 | 8814 | 0.7150 | 0.9165 |
| 0.0 | 40.0 | 9040 | 0.7204 | 0.9182 |
| 0.0022 | 41.0 | 9266 | 0.7127 | 0.9165 |
| 0.0033 | 42.0 | 9492 | 0.7275 | 0.9149 |
| 0.0 | 43.0 | 9718 | 0.7350 | 0.9165 |
| 0.0 | 44.0 | 9944 | 0.7337 | 0.9149 |
| 0.0 | 45.0 | 10170 | 0.7372 | 0.9115 |
| 0.0002 | 46.0 | 10396 | 0.7514 | 0.9165 |
| 0.0 | 47.0 | 10622 | 0.7501 | 0.9115 |
| 0.0 | 48.0 | 10848 | 0.7502 | 0.9149 |
| 0.0 | 49.0 | 11074 | 0.7494 | 0.9098 |
| 0.0 | 50.0 | 11300 | 0.7494 | 0.9115 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2
|