End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: google/vit-base-patch16-224-in21k
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: test_model_7
+  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. -->
+
+# test_model_7
+
+This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.8939
+- F1 Macro: 0.0651
+- F1 Micro: 0.2045
+- F1 Weighted: 0.0913
+- Precision Macro: 0.0760
+- Precision Micro: 0.2045
+- Precision Weighted: 0.1037
+- Recall Macro: 0.1437
+- Recall Micro: 0.2045
+- Recall Weighted: 0.2045
+- Accuracy: 0.2045
+
+## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 2
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Micro | F1 Weighted | Precision Macro | Precision Micro | Precision Weighted | Recall Macro | Recall Micro | Recall Weighted | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:|:---------------:|:---------------:|:------------------:|:------------:|:------------:|:---------------:|:--------:|
+| No log        | 0.8   | 3    | 1.9112          | 0.0464   | 0.1894   | 0.0664      | 0.0281          | 0.1894          | 0.0403             | 0.1323       | 0.1894       | 0.1894          | 0.1894   |
+| No log        | 1.8   | 6    | 1.8938          | 0.0654   | 0.2045   | 0.0917      | 0.0762          | 0.2045          | 0.1040             | 0.1437       | 0.2045       | 0.2045          | 0.2045   |
+
+
+### Framework versions
+
+- Transformers 4.48.1
+- Pytorch 2.5.1+cu124
+- Datasets 3.2.0
+- Tokenizers 0.21.0