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-MultipleCameraFall_UnrealFallDataset
+  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-MultipleCameraFall_UnrealFallDataset
+
+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: 0.1136
+- Accuracy: 0.9736
+
+## 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: 11950
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 1.9014        | 0.1   | 1196  | 2.1529          | 0.5014   |
+| 0.8259        | 1.1   | 2392  | 1.0095          | 0.7478   |
+| 0.4316        | 2.1   | 3588  | 0.6168          | 0.8361   |
+| 0.0665        | 3.1   | 4784  | 0.3693          | 0.8952   |
+| 0.3185        | 4.1   | 5980  | 0.2011          | 0.9456   |
+| 0.2362        | 5.1   | 7176  | 0.2938          | 0.9211   |
+| 0.0728        | 6.1   | 8372  | 0.1560          | 0.9563   |
+| 0.0332        | 7.1   | 9568  | 0.1403          | 0.9620   |
+| 0.0036        | 8.1   | 10764 | 0.1207          | 0.9705   |
+| 0.0026        | 9.1   | 11950 | 0.1136          | 0.9736   |
+
+
+### Framework versions
+
+- Transformers 4.38.0.dev0
+- Pytorch 2.1.2+cu121
+- Datasets 2.16.1
+- Tokenizers 0.15.1

emissions.csv

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+timestamp,experiment_id,project_name,duration,emissions,energy_consumed,country_name,country_iso_code,region,on_cloud,cloud_provider,cloud_region
+2025-01-25T06:23:51,f1cea846-c333-418c-ab0f-0ae41428b1e8,codecarbon,18731.043663740158,0.7316121183894434,1.2265987493758745,Spain,ESP,valencia,N,,