|
---
|
|
license: apache-2.0
|
|
base_model: microsoft/beit-base-patch16-224
|
|
tags:
|
|
- generated_from_trainer
|
|
datasets:
|
|
- imagefolder
|
|
metrics:
|
|
- accuracy
|
|
model-index:
|
|
- name: Karma_3Class_RMSprop_1-e5_10Epoch_Beit-base-patch16_fold5
|
|
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: 0.8448818098813027
|
|
---
|
|
|
|
<!-- 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_1-e5_10Epoch_Beit-base-patch16_fold5
|
|
|
|
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: 1.4092
|
|
- Accuracy: 0.8449
|
|
|
|
## 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 |
|
|
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
|
|
| 0.434 | 1.0 | 2468 | 0.4027 | 0.8307 |
|
|
| 0.321 | 2.0 | 4936 | 0.3800 | 0.8422 |
|
|
| 0.2658 | 3.0 | 7404 | 0.3919 | 0.8538 |
|
|
| 0.1883 | 4.0 | 9872 | 0.5137 | 0.8496 |
|
|
| 0.1083 | 5.0 | 12340 | 0.6774 | 0.8501 |
|
|
| 0.1819 | 6.0 | 14808 | 0.9184 | 0.8469 |
|
|
| 0.1208 | 7.0 | 17276 | 1.1502 | 0.8448 |
|
|
| 0.1339 | 8.0 | 19744 | 1.3133 | 0.8418 |
|
|
| 0.0217 | 9.0 | 22212 | 1.3895 | 0.8434 |
|
|
| 0.0057 | 10.0 | 24680 | 1.4092 | 0.8449 |
|
|
|
|
|
|
### Framework versions
|
|
|
|
- Transformers 4.35.0
|
|
- Pytorch 2.1.0
|
|
- Datasets 2.14.6
|
|
- Tokenizers 0.14.1
|
|
|
