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-URFall_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-URFall_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: 0.1020
+- Accuracy: 0.9717
+
+## 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: 12000
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 1.9074        | 0.1   | 1201  | 2.1151          | 0.5007   |
+| 0.8521        | 1.1   | 2402  | 0.8536          | 0.7784   |
+| 0.3171        | 2.1   | 3603  | 0.6226          | 0.8360   |
+| 0.1523        | 3.1   | 4804  | 0.3766          | 0.8986   |
+| 0.1122        | 4.1   | 6005  | 0.2525          | 0.9274   |
+| 0.0261        | 5.1   | 7206  | 0.2098          | 0.9429   |
+| 0.0707        | 6.1   | 8407  | 0.1900          | 0.9495   |
+| 0.0038        | 7.1   | 9608  | 0.1314          | 0.9657   |
+| 0.0009        | 8.1   | 10809 | 0.1177          | 0.9677   |
+| 0.0011        | 9.1   | 12000 | 0.1020          | 0.9717   |
+
+
+### 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
+2025-01-25T13:26:44,7db87130-189d-4d68-8c89-e57de777ccdd,codecarbon,18898.37783074379,0.7433102872315828,1.2462115454341787,Spain,ESP,valencia,N,,