Model save

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: dog-emotion-classifier
+  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. -->
+
+# dog-emotion-classifier
+
+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: 0.7653
+- Accuracy: 0.8612
+
+## 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: 0.0002
+- train_batch_size: 16
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 10
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 0.5   | 100  | 0.5477          | 0.795    |
+| No log        | 1.0   | 200  | 0.4834          | 0.83     |
+| No log        | 1.5   | 300  | 0.4944          | 0.8263   |
+| No log        | 2.0   | 400  | 0.5020          | 0.8187   |
+| 0.4298        | 2.5   | 500  | 0.5745          | 0.83     |
+| 0.4298        | 3.0   | 600  | 0.6207          | 0.8187   |
+| 0.4298        | 3.5   | 700  | 0.5745          | 0.85     |
+| 0.4298        | 4.0   | 800  | 0.7309          | 0.84     |
+| 0.4298        | 4.5   | 900  | 0.7073          | 0.835    |
+| 0.0585        | 5.0   | 1000 | 0.6339          | 0.8538   |
+| 0.0585        | 5.5   | 1100 | 0.7294          | 0.8413   |
+| 0.0585        | 6.0   | 1200 | 0.7083          | 0.8562   |
+| 0.0585        | 6.5   | 1300 | 0.7272          | 0.8588   |
+| 0.0585        | 7.0   | 1400 | 0.7358          | 0.8588   |
+| 0.0042        | 7.5   | 1500 | 0.7447          | 0.86     |
+| 0.0042        | 8.0   | 1600 | 0.7517          | 0.86     |
+| 0.0042        | 8.5   | 1700 | 0.7581          | 0.8612   |
+| 0.0042        | 9.0   | 1800 | 0.7620          | 0.8612   |
+| 0.0042        | 9.5   | 1900 | 0.7645          | 0.8612   |
+| 0.0012        | 10.0  | 2000 | 0.7653          | 0.8612   |
+
+
+### Framework versions
+
+- Transformers 4.57.1
+- Pytorch 2.8.0+cu126
+- Datasets 4.0.0
+- Tokenizers 0.22.1

model.safetensors

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