Model save

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: facebook/vit-msn-small
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: vit-msn-small-wbc-classifier-0316-cleandataset-10
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: default
+      split: test
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.8561096307575181
+---
+
+<!-- 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-msn-small-wbc-classifier-0316-cleandataset-10
+
+This model is a fine-tuned version of [facebook/vit-msn-small](https://huggingface.co/facebook/vit-msn-small) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3982
+- Accuracy: 0.8561
+
+## 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: 1e-05
+- train_batch_size: 64
+- eval_batch_size: 64
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 256
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
+|:-------------:|:------:|:----:|:---------------:|:--------:|
+| 1.3509        | 0.9730 | 18   | 0.7926          | 0.7876   |
+| 0.6001        | 2.0    | 37   | 0.5589          | 0.8085   |
+| 0.4944        | 2.9730 | 55   | 0.5092          | 0.8226   |
+| 0.462         | 4.0    | 74   | 0.4758          | 0.8260   |
+| 0.4367        | 4.9730 | 92   | 0.4534          | 0.8394   |
+| 0.4175        | 6.0    | 111  | 0.4492          | 0.8462   |
+| 0.4129        | 6.9730 | 129  | 0.4376          | 0.8451   |
+| 0.3956        | 8.0    | 148  | 0.4100          | 0.8515   |
+| 0.3668        | 8.9730 | 166  | 0.4213          | 0.8496   |
+| 0.3752        | 9.7297 | 180  | 0.3982          | 0.8561   |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.1+cu121
+- Datasets 3.2.0
+- Tokenizers 0.19.1

runs/Dec17_13-52-55_ae1aa77fe319/events.out.tfevents.1734443587.ae1aa77fe319.236.16

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