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-gestureUnitV11
+  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-gestureUnitV11
+
+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: 0.9310
+- Loss: 0.3025
+- Accuracy Gunit: 0.8571
+- Accuracy Nothing: 1.0
+
+## 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: 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: 80
+
+### Training results
+
+| Training Loss | Epoch  | Step | Accuracy | Validation Loss | Accuracy Gunit | Accuracy Nothing |
+|:-------------:|:------:|:----:|:--------:|:---------------:|:--------------:|:----------------:|
+| 0.6685        | 0.2125 | 17   | 0.6071   | 0.6297          | 1.0            | 0.2903           |
+| 0.5348        | 1.2125 | 34   | 0.8214   | 0.4292          | 0.6            | 1.0              |
+| 0.3395        | 2.2125 | 51   | 0.7857   | 0.4852          | 0.88           | 0.7097           |
+| 0.3607        | 3.2125 | 68   | 0.8214   | 0.4507          | 0.6            | 1.0              |
+| 0.2436        | 4.15   | 80   | 0.7857   | 0.4433          | 0.76           | 0.8065           |
+
+
+### 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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