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---
license: apache-2.0
base_model: microsoft/beit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: smids_1x_beit_base_rms_00001_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: 0.8964941569282137
---
<!-- 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_1x_beit_base_rms_00001_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: 0.7081
- Accuracy: 0.8965
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3415 | 1.0 | 76 | 0.3600 | 0.8531 |
| 0.1821 | 2.0 | 152 | 0.2813 | 0.8865 |
| 0.1106 | 3.0 | 228 | 0.2915 | 0.8965 |
| 0.0837 | 4.0 | 304 | 0.4355 | 0.8748 |
| 0.0461 | 5.0 | 380 | 0.3524 | 0.8831 |
| 0.0314 | 6.0 | 456 | 0.3471 | 0.9065 |
| 0.052 | 7.0 | 532 | 0.3906 | 0.9032 |
| 0.0094 | 8.0 | 608 | 0.4902 | 0.8998 |
| 0.0397 | 9.0 | 684 | 0.5074 | 0.8848 |
| 0.0068 | 10.0 | 760 | 0.5396 | 0.8965 |
| 0.0009 | 11.0 | 836 | 0.4910 | 0.9032 |
| 0.0007 | 12.0 | 912 | 0.5441 | 0.8982 |
| 0.0176 | 13.0 | 988 | 0.5729 | 0.8965 |
| 0.008 | 14.0 | 1064 | 0.5831 | 0.8965 |
| 0.0023 | 15.0 | 1140 | 0.6581 | 0.8982 |
| 0.0112 | 16.0 | 1216 | 0.6373 | 0.9048 |
| 0.0122 | 17.0 | 1292 | 0.6091 | 0.8982 |
| 0.0218 | 18.0 | 1368 | 0.7005 | 0.8965 |
| 0.0052 | 19.0 | 1444 | 0.6533 | 0.8998 |
| 0.0143 | 20.0 | 1520 | 0.5987 | 0.9048 |
| 0.0047 | 21.0 | 1596 | 0.6407 | 0.8982 |
| 0.005 | 22.0 | 1672 | 0.7577 | 0.8898 |
| 0.0133 | 23.0 | 1748 | 0.7568 | 0.8848 |
| 0.0064 | 24.0 | 1824 | 0.6963 | 0.8915 |
| 0.0056 | 25.0 | 1900 | 0.6832 | 0.8982 |
| 0.0033 | 26.0 | 1976 | 0.6578 | 0.8982 |
| 0.0048 | 27.0 | 2052 | 0.6821 | 0.9032 |
| 0.0003 | 28.0 | 2128 | 0.6751 | 0.8998 |
| 0.0002 | 29.0 | 2204 | 0.6826 | 0.8998 |
| 0.0054 | 30.0 | 2280 | 0.7208 | 0.8965 |
| 0.0234 | 31.0 | 2356 | 0.7169 | 0.8915 |
| 0.0066 | 32.0 | 2432 | 0.7161 | 0.8982 |
| 0.0078 | 33.0 | 2508 | 0.6895 | 0.8982 |
| 0.004 | 34.0 | 2584 | 0.7616 | 0.8982 |
| 0.0117 | 35.0 | 2660 | 0.7211 | 0.9032 |
| 0.0 | 36.0 | 2736 | 0.6772 | 0.8982 |
| 0.0027 | 37.0 | 2812 | 0.6751 | 0.8998 |
| 0.0023 | 38.0 | 2888 | 0.7465 | 0.9082 |
| 0.0025 | 39.0 | 2964 | 0.6434 | 0.9132 |
| 0.0043 | 40.0 | 3040 | 0.6803 | 0.9032 |
| 0.005 | 41.0 | 3116 | 0.6970 | 0.8982 |
| 0.0 | 42.0 | 3192 | 0.6953 | 0.8998 |
| 0.0002 | 43.0 | 3268 | 0.6864 | 0.8982 |
| 0.0001 | 44.0 | 3344 | 0.6955 | 0.9015 |
| 0.0058 | 45.0 | 3420 | 0.7259 | 0.8948 |
| 0.0 | 46.0 | 3496 | 0.7126 | 0.9032 |
| 0.0044 | 47.0 | 3572 | 0.7081 | 0.8965 |
| 0.0032 | 48.0 | 3648 | 0.7104 | 0.8965 |
| 0.0023 | 49.0 | 3724 | 0.7077 | 0.8965 |
| 0.0057 | 50.0 | 3800 | 0.7081 | 0.8965 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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