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: human_action_recognition_model
+  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. -->
+
+# human_action_recognition_model
+
+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: 7.8069
+- Accuracy: 0.0659
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 4
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
+|:-------------:|:------:|:----:|:---------------:|:--------:|
+| 1.3102        | 0.3175 | 500  | 3.5439          | 0.0761   |
+| 0.9861        | 0.6349 | 1000 | 4.1324          | 0.065    |
+| 0.8791        | 0.9524 | 1500 | 4.6708          | 0.0752   |
+| 0.5281        | 1.2698 | 2000 | 5.0605          | 0.0980   |
+| 0.4598        | 1.5873 | 2500 | 6.1627          | 0.0437   |
+| 0.4733        | 1.9048 | 3000 | 5.6746          | 0.0754   |
+| 0.2844        | 2.2222 | 3500 | 6.5390          | 0.0746   |
+| 0.1697        | 2.5397 | 4000 | 6.9396          | 0.0537   |
+| 0.1697        | 2.8571 | 4500 | 7.1644          | 0.0672   |
+| 0.1013        | 3.1746 | 5000 | 7.4083          | 0.0619   |
+| 0.0556        | 3.4921 | 5500 | 7.4283          | 0.0694   |
+| 0.0338        | 3.8095 | 6000 | 7.8069          | 0.0659   |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.0+cu121
+- Datasets 3.0.0
+- Tokenizers 0.19.1

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