Model save

README.md

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+---
+library_name: transformers
+license: cc-by-nc-4.0
+base_model: MCG-NJU/videomae-base
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: VideoMAE_default_fold__3__10_epoch_Aug_batch_1_4_LSA64
+  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. -->
+
+# VideoMAE_default_fold__3__10_epoch_Aug_batch_1_4_LSA64
+
+This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-NJU/videomae-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1592
+- Accuracy: 0.9614
+
+## 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: 2
+- eval_batch_size: 2
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 8
+- optimizer: Use 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
+- training_steps: 2880
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 15.6268       | 0.1   | 288  | 3.6311          | 0.0309   |
+| 8.557         | 1.1   | 576  | 1.2254          | 0.7104   |
+| 2.4113        | 2.1   | 864  | 0.6185          | 0.8494   |
+| 0.9955        | 3.1   | 1152 | 0.3698          | 0.8958   |
+| 0.5989        | 4.1   | 1440 | 0.2324          | 0.9228   |
+| 0.3755        | 5.1   | 1728 | 0.2561          | 0.9382   |
+| 0.2115        | 6.1   | 2016 | 0.1748          | 0.9498   |
+| 0.1498        | 7.1   | 2304 | 0.1669          | 0.9653   |
+| 0.1063        | 8.1   | 2592 | 0.1593          | 0.9614   |
+| 0.0475        | 9.1   | 2880 | 0.1592          | 0.9614   |
+
+
+### Framework versions
+
+- Transformers 4.46.1
+- Pytorch 2.5.1+cu124
+- Datasets 3.1.0
+- Tokenizers 0.20.1

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