🍻 cheers
Browse files- README.md +21 -2
- all_results.json +9 -9
- eval_results.json +5 -5
- runs/Mar22_11-10-32_X5C922065N/events.out.tfevents.1711102248.X5C922065N.52576.16 +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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---
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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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- 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: 1.0
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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: 0.9895
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- Accuracy: 1.0
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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_accuracy": 0
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"eval_loss":
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"eval_runtime": 1.
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"eval_samples_per_second": 24.
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"eval_steps_per_second": 3.
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"total_flos": 9299872197181440.0,
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"train_loss":
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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": 1.0,
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"eval_loss": 0.9895318150520325,
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"eval_runtime": 1.234,
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"eval_samples_per_second": 24.312,
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"eval_steps_per_second": 3.242,
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"total_flos": 9299872197181440.0,
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"train_loss": 1.3567551374435425,
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"train_runtime": 8.4448,
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"train_samples_per_second": 14.21,
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"train_steps_per_second": 1.895
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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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"eval_loss":
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"eval_steps_per_second": 3.
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}
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{
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"epoch": 4.0,
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"eval_accuracy": 1.0,
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"eval_loss": 0.9895318150520325,
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"eval_runtime": 1.234,
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"eval_samples_per_second": 24.312,
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"eval_steps_per_second": 3.242
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}
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runs/Mar22_11-10-32_X5C922065N/events.out.tfevents.1711102248.X5C922065N.52576.16
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version https://git-lfs.github.com/spec/v1
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oid sha256:486e89669e83a33c8982e9c7f61da8b1390e437ad07969ed366f6d8102b94139
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size 405
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train_results.json
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{
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"train_loss":
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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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"epoch": 4.0,
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"total_flos": 9299872197181440.0,
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"train_loss": 1.3567551374435425,
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"train_samples_per_second": 14.21,
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"train_steps_per_second": 1.895
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}
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trainer_state.json
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"log_history": [
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{
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"epoch": 2.5,
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"grad_norm": 2.
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"learning_rate": 7.500000000000001e-05,
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"logging_steps": 10,
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"log_history": [
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"loss": 1.5278,
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