metadata
license: apache-2.0
base_model: microsoft/beit-large-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: Boya2_3Class_RMSprop_1e5_20Epoch_Beit-large-224_fold2
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: 0.8523783488244943
Boya2_3Class_RMSprop_1e5_20Epoch_Beit-large-224_fold2
This model is a fine-tuned version of microsoft/beit-large-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.6527
- Accuracy: 0.8524
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 |
|---|---|---|---|---|
| 0.3607 | 1.0 | 913 | 0.3589 | 0.8565 |
| 0.2545 | 2.0 | 1826 | 0.3889 | 0.8537 |
| 0.1839 | 3.0 | 2739 | 0.5447 | 0.8455 |
| 0.0174 | 4.0 | 3652 | 0.8367 | 0.8548 |
| 0.0719 | 5.0 | 4565 | 1.2411 | 0.8428 |
| 0.0044 | 6.0 | 5478 | 1.3737 | 0.8425 |
| 0.0004 | 7.0 | 6391 | 1.3329 | 0.8529 |
| 0.0003 | 8.0 | 7304 | 1.6015 | 0.8477 |
| 0.0201 | 9.0 | 8217 | 1.6119 | 0.8491 |
| 0.0002 | 10.0 | 9130 | 1.6527 | 0.8524 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.13.2