🍻 cheers
Browse files- README.md +23 -2
- all_results.json +6 -6
- eval_results.json +3 -3
- runs/Mar22_11-05-25_X5C922065N/events.out.tfevents.1711101946.X5C922065N.52576.10 +3 -0
- train_results.json +3 -3
- trainer_state.json +3 -3
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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- generated_from_trainer
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datasets:
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- imagefolder
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model-index:
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- name: vit-finetune-scrap
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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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# vit-finetune-scrap
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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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## 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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- image-classification
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- feature-extraction
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- zero-shot-image-classification
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- generated_from_trainer
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datasets:
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- imagefolder
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metrics:
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- accuracy
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model-index:
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- name: vit-finetune-scrap
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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: d071696/scraps1
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type: imagefolder
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config: default
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split: train
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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: 0.9
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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-finetune-scrap
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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 d071696/scraps1 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.5546
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- Accuracy: 0.9
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## Model description
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all_results.json
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"epoch": 4.0,
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"eval_accuracy": 0.9,
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"eval_loss": 1.5546358823776245,
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"eval_runtime": 1.
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"eval_samples_per_second":
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"eval_steps_per_second":
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"total_flos": 9299872197181440.0,
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"train_loss": 2.0122132897377014,
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"train_runtime":
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"train_samples_per_second":
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"train_steps_per_second": 1.
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}
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"epoch": 4.0,
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"eval_accuracy": 0.9,
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"eval_loss": 1.5546358823776245,
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"eval_runtime": 1.2287,
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"eval_samples_per_second": 24.416,
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"eval_steps_per_second": 3.255,
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"total_flos": 9299872197181440.0,
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"train_loss": 2.0122132897377014,
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"train_runtime": 8.672,
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"train_samples_per_second": 13.838,
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"train_steps_per_second": 1.845
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}
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eval_results.json
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"epoch": 4.0,
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"eval_accuracy": 0.9,
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"eval_loss": 1.5546358823776245,
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"eval_runtime": 1.
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"eval_samples_per_second":
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"eval_steps_per_second":
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}
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"epoch": 4.0,
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"eval_accuracy": 0.9,
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"eval_loss": 1.5546358823776245,
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"eval_runtime": 1.2287,
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"eval_samples_per_second": 24.416,
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"eval_steps_per_second": 3.255
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}
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runs/Mar22_11-05-25_X5C922065N/events.out.tfevents.1711101946.X5C922065N.52576.10
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version https://git-lfs.github.com/spec/v1
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oid sha256:2d0d3e0eb44e5842785dc1a8dcb6dc1b0f6558076db6026c447ed3657e9301af
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size 405
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train_results.json
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"epoch": 4.0,
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"total_flos": 9299872197181440.0,
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"train_loss": 2.0122132897377014,
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"train_runtime":
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"train_samples_per_second":
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"train_steps_per_second": 1.
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}
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"epoch": 4.0,
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"total_flos": 9299872197181440.0,
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"train_loss": 2.0122132897377014,
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"train_runtime": 8.672,
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"train_samples_per_second": 13.838,
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"train_steps_per_second": 1.845
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}
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trainer_state.json
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"step": 16,
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"total_flos": 9299872197181440.0,
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"train_loss": 2.0122132897377014,
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"train_runtime":
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"train_samples_per_second":
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"train_steps_per_second": 1.
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}
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],
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"logging_steps": 10,
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"step": 16,
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"total_flos": 9299872197181440.0,
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"train_loss": 2.0122132897377014,
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"train_runtime": 8.672,
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"train_samples_per_second": 13.838,
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"train_steps_per_second": 1.845
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}
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],
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"logging_steps": 10,
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