Model save

README.md

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+---
+license: cc-by-nc-4.0
+base_model: MCG-NJU/videomae-base
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: videomae-base-finetuned-good-gesturePhaseV11
+  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-base-finetuned-good-gesturePhaseV11
+
+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:
+- Accuracy: 0.9461
+- Loss: 0.1967
+- Accuracy Hold: 1.0
+- Accuracy Stroke: 0.4286
+- Accuracy Recovery: 0.8947
+- Accuracy Preparation: 0.9686
+- Accuracy Unknown: 0.9286
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- training_steps: 1260
+
+### Training results
+
+| Training Loss | Epoch  | Step | Accuracy | Validation Loss | Accuracy Hold | Accuracy Stroke | Accuracy Recovery | Accuracy Preparation | Accuracy Unknown |
+|:-------------:|:------:|:----:|:--------:|:---------------:|:-------------:|:---------------:|:-----------------:|:--------------------:|:----------------:|
+| 1.2097        | 0.1008 | 127  | 0.6900   | 1.0243          | 0.0           | 0.0             | 0.0               | 1.0                  | 0.0              |
+| 0.8           | 1.1008 | 254  | 0.6900   | 0.8717          | 0.0           | 0.0             | 0.0               | 1.0                  | 0.0              |
+| 0.5199        | 2.1008 | 381  | 0.7729   | 0.6725          | 0.0           | 0.0             | 0.1765            | 0.9810               | 0.8636           |
+| 0.3134        | 3.1008 | 508  | 0.8428   | 0.4715          | 0.3077        | 0.0             | 0.4118            | 1.0                  | 0.9091           |
+| 0.1561        | 4.1008 | 635  | 0.8952   | 0.4363          | 0.7692        | 0.0             | 0.7059            | 1.0                  | 0.6818           |
+| 0.0429        | 5.1008 | 762  | 0.9432   | 0.2211          | 0.8846        | 0.5             | 0.7059            | 0.9937               | 0.9545           |
+| 0.2294        | 6.1008 | 889  | 0.9476   | 0.2094          | 0.8846        | 0.1667          | 0.8824            | 1.0                  | 0.9091           |
+| 0.1214        | 7.1008 | 1016 | 0.9607   | 0.1586          | 0.8846        | 0.6667          | 0.8824            | 0.9937               | 0.9545           |
+| 0.1478        | 8.1008 | 1143 | 0.9432   | 0.1607          | 0.8846        | 0.6667          | 0.8824            | 0.9684               | 0.9545           |
+| 0.1156        | 9.0929 | 1260 | 0.9738   | 0.1177          | 1.0           | 0.6667          | 0.8824            | 0.9937               | 0.9545           |
+
+
+### Framework versions
+
+- Transformers 4.41.1
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1

model.safetensors

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