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---
license: apache-2.0
base_model: microsoft/beit-base-patch16-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: beit-base-patch16-224-dmae-va-U5-42E
results: []
---
<!-- 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. -->
# beit-base-patch16-224-dmae-va-U5-42E
This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5797
- Accuracy: 0.8333
## 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: 4e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 42
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| No log | 0.9032 | 7 | 1.2066 | 0.55 |
| 1.5038 | 1.9355 | 15 | 1.2167 | 0.4167 |
| 1.1504 | 2.9677 | 23 | 0.8821 | 0.65 |
| 0.8299 | 4.0 | 31 | 0.6489 | 0.7667 |
| 0.8299 | 4.9032 | 38 | 0.5797 | 0.8333 |
| 0.5887 | 5.9355 | 46 | 0.6618 | 0.75 |
| 0.3965 | 6.9677 | 54 | 0.6531 | 0.7833 |
| 0.3089 | 8.0 | 62 | 0.7609 | 0.7 |
| 0.3089 | 8.9032 | 69 | 0.8609 | 0.6833 |
| 0.2393 | 9.9355 | 77 | 0.6910 | 0.7833 |
| 0.1928 | 10.9677 | 85 | 0.7774 | 0.8 |
| 0.1993 | 12.0 | 93 | 0.8424 | 0.7833 |
| 0.165 | 12.9032 | 100 | 0.7478 | 0.7667 |
| 0.165 | 13.9355 | 108 | 0.7573 | 0.75 |
| 0.1117 | 14.9677 | 116 | 0.8059 | 0.8167 |
| 0.1171 | 16.0 | 124 | 0.8982 | 0.7667 |
| 0.0961 | 16.9032 | 131 | 0.9133 | 0.8 |
| 0.0961 | 17.9355 | 139 | 0.9121 | 0.7667 |
| 0.1359 | 18.9677 | 147 | 0.9297 | 0.8 |
| 0.0981 | 20.0 | 155 | 1.0124 | 0.7333 |
| 0.0817 | 20.9032 | 162 | 0.9628 | 0.75 |
| 0.0976 | 21.9355 | 170 | 0.9664 | 0.7667 |
| 0.0976 | 22.9677 | 178 | 0.7980 | 0.8167 |
| 0.0899 | 24.0 | 186 | 0.8366 | 0.7667 |
| 0.1052 | 24.9032 | 193 | 0.9160 | 0.7667 |
| 0.0817 | 25.9355 | 201 | 0.9701 | 0.7667 |
| 0.0817 | 26.9677 | 209 | 0.9995 | 0.75 |
| 0.0886 | 28.0 | 217 | 0.8483 | 0.8 |
| 0.0766 | 28.9032 | 224 | 0.8954 | 0.7833 |
| 0.0923 | 29.9355 | 232 | 0.9606 | 0.7833 |
| 0.0579 | 30.9677 | 240 | 0.9958 | 0.75 |
| 0.0579 | 32.0 | 248 | 0.9665 | 0.7833 |
| 0.0707 | 32.9032 | 255 | 1.0259 | 0.7667 |
| 0.0756 | 33.9355 | 263 | 1.0627 | 0.75 |
| 0.0528 | 34.9677 | 271 | 1.0508 | 0.7667 |
| 0.0528 | 36.0 | 279 | 1.0998 | 0.7667 |
| 0.0706 | 36.9032 | 286 | 1.0694 | 0.75 |
| 0.0658 | 37.9355 | 294 | 1.0561 | 0.7667 |
### Framework versions
- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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