End of training
Browse files- README.md +76 -0
- model.safetensors +1 -1
README.md
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---
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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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metrics:
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- accuracy
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model-index:
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- name: Image-Classifier-Pokemons
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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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should probably proofread and complete it, then remove this comment. -->
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# Image-Classifier-Pokemons
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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 an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.8369
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- Accuracy: 0.8921
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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: 5e-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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- gradient_accumulation_steps: 4
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- total_train_batch_size: 64
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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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- lr_scheduler_warmup_ratio: 0.1
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- training_steps: 1200
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-------:|:----:|:---------------:|:--------:|
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| 4.9198 | 0.9943 | 87 | 4.8889 | 0.1158 |
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| 4.4617 | 2.0 | 175 | 4.4093 | 0.5868 |
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| 3.869 | 2.9943 | 262 | 3.8642 | 0.7534 |
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| 3.4201 | 4.0 | 350 | 3.4278 | 0.8170 |
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| 3.0186 | 4.9943 | 437 | 3.0832 | 0.8220 |
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| 2.6769 | 6.0 | 525 | 2.7755 | 0.8578 |
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| 2.4469 | 6.9943 | 612 | 2.5311 | 0.8635 |
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| 2.1796 | 8.0 | 700 | 2.3141 | 0.8771 |
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| 2.0105 | 8.9943 | 787 | 2.1620 | 0.8849 |
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| 1.8571 | 10.0 | 875 | 2.0283 | 0.8885 |
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| 1.7549 | 10.9943 | 962 | 1.9372 | 0.8856 |
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| 1.6934 | 12.0 | 1050 | 1.8779 | 0.8949 |
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| 1.6377 | 12.9943 | 1137 | 1.8180 | 0.9006 |
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| 1.6182 | 13.7143 | 1200 | 1.8369 | 0.8921 |
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### Framework versions
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- Transformers 4.40.2
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- Pytorch 2.2.1+cu121
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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model.safetensors
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