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---
license: apache-2.0
base_model: microsoft/beit-large-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: Karma_3Class_RMSprop_1e5_20Epoch_Beit-large-224_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: 0.8561998578247182
---
<!-- 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. -->
# Karma_3Class_RMSprop_1e5_20Epoch_Beit-large-224_fold1
This model is a fine-tuned version of [microsoft/beit-large-patch16-224](https://huggingface.co/microsoft/beit-large-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6210
- Accuracy: 0.8562
## 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: 16
- eval_batch_size: 16
- 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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.314 | 1.0 | 2469 | 0.3707 | 0.8430 |
| 0.2191 | 2.0 | 4938 | 0.3892 | 0.8507 |
| 0.1908 | 3.0 | 7407 | 0.4759 | 0.8516 |
| 0.0575 | 4.0 | 9876 | 0.6918 | 0.8571 |
| 0.0175 | 5.0 | 12345 | 1.0455 | 0.8526 |
| 0.1052 | 6.0 | 14814 | 1.2531 | 0.8548 |
| 0.0016 | 7.0 | 17283 | 1.3936 | 0.8554 |
| 0.0 | 8.0 | 19752 | 1.5161 | 0.8563 |
| 0.0218 | 9.0 | 22221 | 1.6233 | 0.8582 |
| 0.0 | 10.0 | 24690 | 1.6210 | 0.8562 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.13.2
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