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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
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