Model save

README.md

@@ -0,0 +1,54 @@
+---
+library_name: peft
+license: apache-2.0
+base_model: google/vit-base-patch16-224-in21k
+tags:
+- generated_from_trainer
+model-index:
+- name: vit-base-patch16-224-in21k-finetuned-lora-food101
+  results: []
+---
+
+<!-- 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. -->
+
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/jsphd/week10_tutorial/runs/pb2bbdxd)
+# vit-base-patch16-224-in21k-finetuned-lora-food101
+
+This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
+
+## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 5
+- mixed_precision_training: Native AMP
+
+### Framework versions
+
+- PEFT 0.13.2
+- Transformers 4.48.0.dev0
+- Pytorch 2.5.1+cu121
+- Datasets 3.1.0
+- Tokenizers 0.21.0

adapter_model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:8c658c8927064fed97575136de92936f554cbce9a81954736d5f9590511c999c
+oid sha256:74a05df5538c60164a83db6ab4751ac7145a83ad2c31ea2ad0abe7f2df148a49
 size 2677140