barghavani
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End of training
Browse files- README.md +16 -9
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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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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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# Cheese_xray
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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: 0.
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- Accuracy: 0.
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## Model description
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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 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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### Framework versions
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license: apache-2.0
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base_model: barghavani/Cheese_xray
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tags:
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- generated_from_trainer
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datasets:
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.8883161512027491
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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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# Cheese_xray
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This model is a fine-tuned version of [barghavani/Cheese_xray](https://huggingface.co/barghavani/Cheese_xray) on the chest-xray-classification dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2827
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- Accuracy: 0.8883
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## Model description
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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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| 0.3993 | 0.99 | 63 | 0.4364 | 0.7165 |
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| 0.3454 | 1.99 | 127 | 0.3947 | 0.7680 |
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| 0.3327 | 3.0 | 191 | 0.3582 | 0.8591 |
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| 0.3329 | 4.0 | 255 | 0.3371 | 0.8746 |
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| 0.2992 | 4.99 | 318 | 0.3449 | 0.8643 |
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| 0.3289 | 5.99 | 382 | 0.3172 | 0.8832 |
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| 0.3309 | 7.0 | 446 | 0.2956 | 0.8935 |
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| 0.2875 | 8.0 | 510 | 0.2911 | 0.8883 |
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| 0.2764 | 8.99 | 573 | 0.2884 | 0.9124 |
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| 0.265 | 9.88 | 630 | 0.2827 | 0.8883 |
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### Framework versions
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model.safetensors
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