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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-finetuned-good-gesturePhaseV10
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-finetuned-good-gesturePhaseV10
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:
- Accuracy: 0.9253
- Loss: 0.3122
- Accuracy Hold: 1.0
- Accuracy Stroke: 0.4286
- Accuracy Recovery: 0.7895
- Accuracy Preparation: 1.0
- Accuracy Unknown: 0.6429
## 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: 630
### Training results
| Training Loss | Epoch | Step | Accuracy | Validation Loss | Accuracy Hold | Accuracy Stroke | Accuracy Recovery | Accuracy Preparation | Accuracy Unknown |
|:-------------:|:------:|:----:|:--------:|:---------------:|:-------------:|:---------------:|:-----------------:|:--------------------:|:----------------:|
| 1.1344 | 0.2016 | 127 | 0.6900 | 1.0021 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 |
| 0.5961 | 1.2016 | 254 | 0.7948 | 0.6022 | 0.2692 | 0.0 | 0.0588 | 0.9873 | 0.8182 |
| 0.3453 | 2.2016 | 381 | 0.8777 | 0.3925 | 0.8077 | 0.0 | 0.4118 | 0.9747 | 0.8636 |
| 0.1551 | 3.2016 | 508 | 0.9432 | 0.2178 | 0.9615 | 0.1667 | 0.7059 | 0.9937 | 0.9545 |
| 0.1213 | 4.1937 | 630 | 0.9476 | 0.2032 | 0.9615 | 0.6667 | 0.7059 | 1.0 | 0.8182 |
### Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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