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--- |
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license: apache-2.0 |
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base_model: microsoft/resnet-18 |
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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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model-index: |
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- name: resnet-18-resnet-18 |
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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: 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: 0.3541666666666667 |
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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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# resnet-18-resnet-18 |
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This model is a fine-tuned version of [microsoft/resnet-18](https://huggingface.co/microsoft/resnet-18) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 5878685290980833992550249398272.0000 |
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- Accuracy: 0.3542 |
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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: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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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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- num_epochs: 10 |
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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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| No log | 0.8889 | 6 | 5256596847186447919144532705280.0000 | 0.3542 | |
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| 6252348666680642391375611953152.0000 | 1.9259 | 13 | 5816409290772115792559022800896.0000 | 0.3542 | |
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| 5941338476045271956843984322560.0000 | 2.9630 | 20 | 5569209952566045840858865991680.0000 | 0.3542 | |
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| 5941338476045271956843984322560.0000 | 4.0 | 27 | 5764530657074993210784856670208.0000 | 0.3542 | |
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| 5978113032337293509815187800064.0000 | 4.8889 | 33 | 5717174614869048956753266343936.0000 | 0.3542 | |
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| 6377920275134342219963975073792.0000 | 5.9259 | 40 | 5885479454087068208512098107392.0000 | 0.3542 | |
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| 6377920275134342219963975073792.0000 | 6.9630 | 47 | 5693683372805207289944963284992.0000 | 0.3542 | |
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| 6201930657158778429750307192832.0000 | 8.0 | 54 | 5815479022353922335409086398464.0000 | 0.3542 | |
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| 6266525497982100125501481811968.0000 | 8.8889 | 60 | 5878685290980833992550249398272.0000 | 0.3542 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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