metadata
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_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: 0.8465522494160658
Karma_3Class_RMSprop_1-e5_10Epoch_Beit-base-patch16_fold1
This model is a fine-tuned version of microsoft/beit-base-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.4379
- Accuracy: 0.8466
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 |
---|---|---|---|---|
0.4006 | 1.0 | 2469 | 0.4086 | 0.8326 |
0.3402 | 2.0 | 4938 | 0.3814 | 0.8446 |
0.251 | 3.0 | 7407 | 0.4352 | 0.8428 |
0.1756 | 4.0 | 9876 | 0.4819 | 0.8441 |
0.0538 | 5.0 | 12345 | 0.7537 | 0.8447 |
0.1652 | 6.0 | 14814 | 0.9357 | 0.8438 |
0.0783 | 7.0 | 17283 | 1.1869 | 0.8391 |
0.0039 | 8.0 | 19752 | 1.2745 | 0.8451 |
0.0011 | 9.0 | 22221 | 1.4099 | 0.8449 |
0.0134 | 10.0 | 24690 | 1.4379 | 0.8466 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1