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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: timm/resnet101.a1_in1k |
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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: vit-base-beans |
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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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# vit-base-beans |
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This model is a fine-tuned version of [timm/resnet101.a1_in1k](https://huggingface.co./timm/resnet101.a1_in1k) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5027 |
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- Accuracy: 0.8571 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 1337 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 20.0 |
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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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| 1.07 | 1.0 | 130 | 1.0683 | 0.4135 | |
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| 1.0523 | 2.0 | 260 | 1.0356 | 0.6241 | |
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| 1.0439 | 3.0 | 390 | 1.0045 | 0.6617 | |
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| 1.0056 | 4.0 | 520 | 0.9671 | 0.7293 | |
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| 0.9853 | 5.0 | 650 | 0.9245 | 0.7895 | |
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| 0.9581 | 6.0 | 780 | 0.8744 | 0.7820 | |
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| 0.9044 | 7.0 | 910 | 0.8172 | 0.7820 | |
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| 0.869 | 8.0 | 1040 | 0.7737 | 0.8271 | |
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| 0.8804 | 9.0 | 1170 | 0.7098 | 0.8271 | |
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| 0.7757 | 10.0 | 1300 | 0.6705 | 0.8120 | |
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| 0.7694 | 11.0 | 1430 | 0.6382 | 0.8571 | |
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| 0.7966 | 12.0 | 1560 | 0.6088 | 0.7895 | |
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| 0.7425 | 13.0 | 1690 | 0.5724 | 0.8496 | |
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| 0.7698 | 14.0 | 1820 | 0.5665 | 0.8195 | |
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| 0.6632 | 15.0 | 1950 | 0.5308 | 0.8571 | |
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| 0.6162 | 16.0 | 2080 | 0.5262 | 0.8346 | |
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| 0.6128 | 17.0 | 2210 | 0.5081 | 0.8421 | |
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| 0.685 | 18.0 | 2340 | 0.4913 | 0.8571 | |
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| 0.6614 | 19.0 | 2470 | 0.4937 | 0.8496 | |
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| 0.6934 | 20.0 | 2600 | 0.5027 | 0.8571 | |
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### Framework versions |
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- Transformers 4.47.0.dev0 |
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- Pytorch 2.5.0+cu118 |
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- Datasets 2.21.0 |
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- Tokenizers 0.20.0 |
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