Model save
Browse files- README.md +90 -0
- all_results.json +8 -0
- train_results.json +8 -0
README.md
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---
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library_name: transformers
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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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metrics:
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- accuracy
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- f1
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model-index:
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- name: got-model
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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: imagefolder
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type: imagefolder
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config: default
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split: test
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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: 0.9428571428571428
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- name: F1
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type: f1
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value: 0.9442260195944405
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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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# got-model
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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 imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1971
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- Accuracy: 0.9429
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- F1: 0.9442
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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: 2e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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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: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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| 0.073 | 1.0 | 42 | 0.2416 | 0.9238 | 0.9250 |
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| 0.061 | 2.0 | 84 | 0.2160 | 0.9333 | 0.9345 |
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| 0.0543 | 3.0 | 126 | 0.2114 | 0.9429 | 0.9432 |
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| 0.0497 | 4.0 | 168 | 0.2028 | 0.9429 | 0.9442 |
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| 0.046 | 5.0 | 210 | 0.1985 | 0.9429 | 0.9442 |
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| 0.0435 | 6.0 | 252 | 0.2009 | 0.9429 | 0.9442 |
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| 0.0414 | 7.0 | 294 | 0.1976 | 0.9429 | 0.9442 |
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| 0.0402 | 8.0 | 336 | 0.1978 | 0.9429 | 0.9442 |
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| 0.0391 | 9.0 | 378 | 0.1967 | 0.9429 | 0.9442 |
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| 0.0385 | 10.0 | 420 | 0.1971 | 0.9429 | 0.9442 |
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### Framework versions
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- Transformers 4.45.2
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- Pytorch 2.4.1+cu121
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- Datasets 3.0.1
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- Tokenizers 0.20.0
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all_results.json
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{
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"epoch": 10.0,
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"total_flos": 5.130291560557363e+17,
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"train_loss": 0.04840113861220224,
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"train_runtime": 1424.2891,
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"train_samples_per_second": 4.648,
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"train_steps_per_second": 0.295
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}
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train_results.json
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{
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"epoch": 10.0,
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"total_flos": 5.130291560557363e+17,
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"train_loss": 0.04840113861220224,
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"train_runtime": 1424.2891,
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"train_samples_per_second": 4.648,
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"train_steps_per_second": 0.295
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}
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