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-groub9-finetuned-SLT-subset
+  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-groub9-finetuned-SLT-subset
+
+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: 2.7934
+- Accuracy: 0.2381
+
+## 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: 4
+- eval_batch_size: 4
+- 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: 20
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 0.3   | 6    | 2.9200          | 0.1429   |
+| 3.1357        | 1.3   | 12   | 2.8631          | 0.1905   |
+| 3.1357        | 2.3   | 18   | 2.8002          | 0.2381   |
+| 2.9058        | 3.1   | 20   | 2.7934          | 0.2381   |
+
+
+### Framework versions
+
+- Transformers 4.33.0
+- Pytorch 2.0.0+cpu
+- Datasets 2.1.0
+- Tokenizers 0.13.3

pytorch_model.bin

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