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vit-base-patch16-224-in21k-lora
palsp/vit-base-patch16-224-in21k-lora
vit-base-patch16-224-in21k-lora is a machine learning model from palsp. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. 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
- Library
- peft
- License
- apache-2.0
- Access
- Public
- Created
- Aug 25, 2024
- Updated
- Aug 25, 2024
- SHA
- 40fb9113
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. -->
vit-base-patch16-224-in21k-lora
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3368
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: 0.005
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.8192 | 1.0 | 148 | 0.4721 |
| 0.7016 | 2.0 | 296 | 0.4040 |
| 0.6583 | 3.0 | 444 | 0.3712 |
| 0.5792 | 4.0 | 592 | 0.3481 |
| 0.5452 | 5.0 | 740 | 0.3368 |
Framework versions
- PEFT 0.12.0
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
- Library
- peft
- License
- apache-2.0
- Created
- Aug 25, 2024
- Updated
- Aug 25, 2024