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beit-base-patch16-224-pt22k-ft22k-finetuned-barkley
alyzbane/beit-base-patch16-224-pt22k-ft22k-finetuned-barkley
beit-base-patch16-224-pt22k-ft22k-finetuned-barkley is a image classification model from alyzbane. Use it when you need a label for an image. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Image Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- beit
- Access
- Public
- Created
- Oct 19, 2024
- Updated
- Oct 19, 2024
- SHA
- 229def09
Base models
Model card
From the Hugging Face model README
<!-- 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. -->
beit-base-patch16-224-pt22k-ft22k-finetuned-barkley
This model is a fine-tuned version of microsoft/beit-base-patch16-224-pt22k-ft22k on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0079
- Precision: 1.0
- Recall: 1.0
- F1: 1.0
- Accuracy: 1.0
- Top1 Accuracy: 1.0
- Error Rate: 0.0
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: 0.0002
- train_batch_size: 32
- eval_batch_size: 32
- 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: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | Top1 Accuracy | Error Rate |
|---|---|---|---|---|---|---|---|---|---|
| 1.5547 | 1.0 | 38 | 1.4018 | 0.5683 | 0.4539 | 0.4240 | 0.4728 | 0.4539 | 0.5272 |
| 1.1732 | 2.0 | 76 | 0.9193 | 0.8095 | 0.7961 | 0.7985 | 0.8077 | 0.7961 | 0.1923 |
| 0.6764 | 3.0 | 114 | 0.3644 | 0.9488 | 0.9474 | 0.9470 | 0.9483 | 0.9474 | 0.0517 |
| 0.2566 | 4.0 | 152 | 0.0871 | 0.9937 | 0.9934 | 0.9934 | 0.9944 | 0.9934 | 0.0056 |
| 0.1014 | 5.0 | 190 | 0.0533 | 0.9809 | 0.9803 | 0.9802 | 0.9811 | 0.9803 | 0.0189 |
| 0.0538 | 6.0 | 228 | 0.0208 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 |
| 0.0304 | 7.0 | 266 | 0.0079 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 |
| 0.0571 | 8.0 | 304 | 0.0088 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 |
| 0.0608 | 9.0 | 342 | 0.0226 | 0.9936 | 0.9934 | 0.9934 | 0.9933 | 0.9934 | 0.0067 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.3.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
- Task
- Image Classification
- Library
- transformers
- Type
- beit
- License
- apache-2.0
- Created
- Oct 19, 2024
- Updated
- Oct 19, 2024