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End of training
Browse files- README.md +15 -16
- model.safetensors +1 -1
README.md
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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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- name: F1
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type: f1
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value: 0.
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- name: Precision
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type: precision
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value: 0.
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- name: Recall
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type: recall
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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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This model was trained from scratch on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Accuracy: 0.
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- F1: 0.
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- Precision: 0.
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- Recall: 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: 1e-
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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 | Accuracy | F1 | Precision | Recall |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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| 0.206 | 5.0 | 9850 | 0.1768 | 0.9254 | 0.9052 | 0.9233 | 0.8879 |
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### Framework versions
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.6404109589041096
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- name: F1
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type: f1
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value: 0.5016949152542373
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- name: Precision
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type: precision
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value: 0.6290224650880388
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- name: Recall
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type: recall
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value: 0.41723721304873135
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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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This model was trained from scratch on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.7208
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- Accuracy: 0.6404
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- F1: 0.5017
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- Precision: 0.6290
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- Recall: 0.4172
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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: 1e-06
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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: 4
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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| 0.4992 | 1.0 | 2015 | 0.7072 | 0.6189 | 0.4517 | 0.6009 | 0.3619 |
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| 0.4581 | 2.0 | 4031 | 0.7145 | 0.6383 | 0.4787 | 0.6387 | 0.3828 |
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| 0.4229 | 3.0 | 6047 | 0.7146 | 0.6434 | 0.5077 | 0.6329 | 0.4238 |
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| 0.4096 | 4.0 | 8060 | 0.7208 | 0.6404 | 0.5017 | 0.6290 | 0.4172 |
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### Framework versions
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model.safetensors
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