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---
license: apache-2.0
base_model: microsoft/beit-base-patch16-224-pt22k-ft22k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Train-Test-Augmentation-V44-beit-base
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. -->
# Train-Test-Augmentation-V44-beit-base
This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5318
- Accuracy: 0.8142
## 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: 5e-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: 5
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.6031 | 0.9825 | 28 | 0.9362 | 0.7132 |
| 0.5124 | 2.0 | 57 | 0.6364 | 0.7933 |
| 0.2676 | 2.9825 | 85 | 0.5382 | 0.8125 |
| 0.1263 | 4.0 | 114 | 0.5486 | 0.8114 |
| 0.0833 | 4.9123 | 140 | 0.5318 | 0.8142 |
### Framework versions
- Transformers 4.41.1
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1