End of training
Browse files- README.md +68 -0
- adapter_model.bin +1 -1
README.md
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---
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license: apache-2.0
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base_model: google/vit-base-patch16-224-in21k
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tags:
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- generated_from_trainer
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datasets:
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- food101
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metrics:
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- accuracy
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model-index:
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- name: vit-base-patch16-224-in21k-finetuned-lora-food101
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# vit-base-patch16-224-in21k-finetuned-lora-food101
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This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the food101 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1158
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- Accuracy: 0.962
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.005
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- train_batch_size: 128
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- eval_batch_size: 128
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 512
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 5
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| No log | 1.0 | 9 | 0.1536 | 0.95 |
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| 0.2548 | 2.0 | 18 | 0.1263 | 0.96 |
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| 0.1404 | 3.0 | 27 | 0.1158 | 0.962 |
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| 0.1214 | 4.0 | 36 | 0.1232 | 0.96 |
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| 0.1238 | 5.0 | 45 | 0.1177 | 0.96 |
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### Framework versions
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- Transformers 4.33.2
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.5
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- Tokenizers 0.13.3
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adapter_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size 2688263
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version https://git-lfs.github.com/spec/v1
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oid sha256:35950269c1d856b276cf7917daac3a79ad53800a176f1d25118fe9b2904edcc0
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size 2688263
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