Model save

README.md

@@ -0,0 +1,74 @@
+---
+license: apache-2.0
+base_model: DunnBC22/vit-base-patch16-224-in21k_covid_19_ct_scans
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: vit-base-patch16-224-in21k_covid_19_ct_scans-finetuned-RCC
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# vit-base-patch16-224-in21k_covid_19_ct_scans-finetuned-RCC
+
+This model is a fine-tuned version of [DunnBC22/vit-base-patch16-224-in21k_covid_19_ct_scans](https://huggingface.co/DunnBC22/vit-base-patch16-224-in21k_covid_19_ct_scans) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3235
+- Accuracy: 0.9032
+- Precision: 0.9032
+- Recall: 1.0
+- F1: 0.4746
+- Auc: 0.5
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 5e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 128
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Auc |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:---:|
+| No log        | 1.0   | 7    | 0.3327          | 0.9032   | 0.9032    | 1.0    | 0.4746 | 0.5 |
+| 0.3866        | 2.0   | 14   | 0.3213          | 0.9032   | 0.9032    | 1.0    | 0.4746 | 0.5 |
+| 0.2647        | 3.0   | 21   | 0.3226          | 0.9032   | 0.9032    | 1.0    | 0.4746 | 0.5 |
+| 0.2647        | 4.0   | 28   | 0.3246          | 0.9032   | 0.9032    | 1.0    | 0.4746 | 0.5 |
+| 0.2593        | 5.0   | 35   | 0.3235          | 0.9032   | 0.9032    | 1.0    | 0.4746 | 0.5 |
+
+
+### Framework versions
+
+- Transformers 4.41.1
+- Pytorch 2.0.0+cu117
+- Datasets 2.19.1
+- Tokenizers 0.19.1

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:29f228df3d99ae7ebf5e6defca6ef82583f16d3b233c75232c8398160110f2e0
+oid sha256:bf579d8d432897475479bd8b99f9b0e80634bf5f6015cbaf759efc00d151cd74
 size 343223968

runs/May27_17-11-52_RTX3090/events.out.tfevents.1716797516.RTX3090.8398.0

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:a5be2460dc82e26b5db90968c0888c95388ec059e2817a7b038801df3e4e6c87
-size 7506
+oid sha256:fbe216952598c83d9f9af21613ed6a089f52b5112bd10d53b9e76cccd6075997
+size 8570