End of training
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- model.safetensors +1 -1
README.md
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---
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license: apache-2.0
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base_model:
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tags:
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- generated_from_trainer
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datasets:
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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.
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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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# urinary_carcinoma_classifier
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This model is a fine-tuned version of [
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It achieves the following results on the evaluation set:
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- Loss:
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- Accuracy: 0.
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-
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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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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs:
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### Training results
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| Training Loss | Epoch | Step | Validation Loss
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| No log | 1.0 | 1 |
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| No log | 2.0 | 2 |
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| No log | 3.0 | 3 |
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| No log | 4.0 | 4 | 0.6885 | 0.5 |
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| No log | 5.0 | 5 | 0.6830 | 0.625 |
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### Framework versions
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---
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license: apache-2.0
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base_model: microsoft/resnet-50
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tags:
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- generated_from_trainer
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datasets:
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name: imagefolder
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type: imagefolder
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config: default
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split: train[:18]
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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: 0.5
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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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# urinary_carcinoma_classifier
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This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 145167345715929860710353977110167552.0000
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- Accuracy: 0.5
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## Model description
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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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- 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: 3
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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 | 1.0 | 1 | 171619846545786152085242447388475392.0000 | 0.5 |
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| No log | 2.0 | 2 | 216416222105935722637923733961965568.0000 | 0.75 |
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| No log | 3.0 | 3 | 145167345715929860710353977110167552.0000 | 0.5 |
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### Framework versions
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model.safetensors
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