🍻 cheers
Browse files- README.md +7 -1
- all_results.json +9 -9
- eval_results.json +5 -5
- runs/Mar22_11-09-00_X5C922065N/events.out.tfevents.1711102156.X5C922065N.52576.14 +3 -0
- train_results.json +4 -4
- trainer_state.json +6 -6
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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# 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-feature-extraction
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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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# 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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{
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"epoch": 4.0,
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"eval_loss": 1.
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"total_flos": 9299872197181440.0,
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"train_loss": 2.
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"train_runtime": 8.
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"train_samples_per_second": 14.
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"train_steps_per_second": 1.
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}
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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": 1.2259,
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"eval_samples_per_second": 24.472,
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"eval_steps_per_second": 3.263,
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"total_flos": 9299872197181440.0,
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"train_loss": 2.0122132897377014,
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"train_runtime": 8.5249,
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"train_samples_per_second": 14.076,
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"train_steps_per_second": 1.877
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}
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eval_results.json
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{
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"epoch": 4.0,
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"eval_accuracy": 0.
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{
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"epoch": 4.0,
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}
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runs/Mar22_11-09-00_X5C922065N/events.out.tfevents.1711102156.X5C922065N.52576.14
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version https://git-lfs.github.com/spec/v1
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oid sha256:5ee4bf667e845d17e9260b4100c5fe9fc58841deea9e7e2b40383e4bed65b74f
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size 405
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train_results.json
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{
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"train_loss": 2.
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"train_steps_per_second": 1.877
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}
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trainer_state.json
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"log_history": [
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"logging_steps": 10,
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"train_steps_per_second": 1.877
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