zazazaChiang
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Model save
Browse files- README.md +19 -6
- config.json +0 -1
- training_args.bin +1 -1
README.md
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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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- image-classification
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- vision
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: vit-base-beans
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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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@@ -18,10 +31,10 @@ should probably proofread and complete it, then remove this comment. -->
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# vit-base-beans
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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
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It achieves the following results on the evaluation set:
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## Model description
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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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- arrow
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metrics:
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- accuracy
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model-index:
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- name: vit-base-beans
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results:
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- task:
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name: Image Classification
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type: image-classification
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dataset:
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name: arrow
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type: arrow
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config: default
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split: validation
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args: default
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.9774436090225563
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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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# vit-base-beans
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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 arrow dataset.
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It achieves the following results on the evaluation set:
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- Accuracy: 0.9774
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- Loss: 0.0842
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## Model description
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config.json
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"num_channels": 3,
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"num_hidden_layers": 12,
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"patch_size": 16,
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"problem_type": "single_label_classification",
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"qkv_bias": true,
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"torch_dtype": "float32",
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"transformers_version": "4.44.2"
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"num_channels": 3,
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"num_hidden_layers": 12,
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"patch_size": 16,
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"qkv_bias": true,
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"torch_dtype": "float32",
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"transformers_version": "4.44.2"
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size 5240
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version https://git-lfs.github.com/spec/v1
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size 5240
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