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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
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
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: 0.1097
- Accuracy: 0.9743
## 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: 11820
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 2.1366 | 0.1 | 1183 | 1.9949 | 0.5648 |
| 0.8345 | 1.1 | 2366 | 0.8534 | 0.7909 |
| 0.4507 | 2.1 | 3549 | 0.5013 | 0.8644 |
| 0.2105 | 3.1 | 4732 | 0.3949 | 0.8949 |
| 0.1062 | 4.1 | 5915 | 0.2903 | 0.9258 |
| 0.0427 | 5.1 | 7098 | 0.2665 | 0.9298 |
| 0.0028 | 6.1 | 8281 | 0.2535 | 0.9379 |
| 0.0018 | 7.1 | 9464 | 0.1895 | 0.9558 |
| 0.0133 | 8.1 | 10647 | 0.1128 | 0.9736 |
| 0.1176 | 9.1 | 11820 | 0.1097 | 0.9743 |
### Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
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