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---
library_name: transformers
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-cart-activity-v2-imagefolder
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-cart-activity-v2-imagefolder
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: 0.1807
- Accuracy: 0.9533
## 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: 2
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 17145
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:-----:|:---------------:|:--------:|
| 0.3978 | 0.0334 | 572 | 0.9201 | 0.5969 |
| 0.294 | 1.0334 | 1144 | 0.3255 | 0.9027 |
| 0.5046 | 2.0334 | 1716 | 0.6951 | 0.7712 |
| 0.3563 | 3.0334 | 2288 | 0.2648 | 0.9284 |
| 0.4592 | 4.0334 | 2860 | 0.2469 | 0.9167 |
| 0.1586 | 5.0334 | 3432 | 0.2294 | 0.9354 |
| 0.1798 | 6.0334 | 4004 | 0.2167 | 0.9346 |
| 0.3834 | 7.0334 | 4576 | 0.2334 | 0.9292 |
| 0.1425 | 8.0334 | 5148 | 0.2864 | 0.9253 |
| 0.1253 | 9.0334 | 5720 | 0.2605 | 0.9183 |
| 0.2152 | 10.0334 | 6292 | 0.2687 | 0.9276 |
| 0.1605 | 11.0334 | 6864 | 0.2657 | 0.9237 |
| 0.1927 | 12.0334 | 7436 | 0.2134 | 0.9424 |
| 0.1003 | 13.0334 | 8008 | 0.2687 | 0.9300 |
| 0.2421 | 14.0334 | 8580 | 0.2345 | 0.9307 |
| 0.1248 | 15.0334 | 9152 | 0.3142 | 0.9136 |
| 0.2701 | 16.0334 | 9724 | 0.2174 | 0.9409 |
| 0.1817 | 17.0334 | 10296 | 0.2328 | 0.9416 |
| 0.1447 | 18.0334 | 10868 | 0.2165 | 0.9393 |
| 0.1101 | 19.0334 | 11440 | 0.2811 | 0.9300 |
| 0.1832 | 20.0334 | 12012 | 0.2230 | 0.9424 |
| 0.1064 | 21.0334 | 12584 | 0.1843 | 0.9479 |
| 0.2109 | 22.0334 | 13156 | 0.2523 | 0.9323 |
| 0.0486 | 23.0334 | 13728 | 0.2485 | 0.9377 |
| 0.1455 | 24.0334 | 14300 | 0.1807 | 0.9533 |
| 0.0695 | 25.0334 | 14872 | 0.2349 | 0.9393 |
| 0.2897 | 26.0334 | 15444 | 0.2229 | 0.9393 |
| 0.0949 | 27.0334 | 16016 | 0.2156 | 0.9486 |
| 0.0849 | 28.0334 | 16588 | 0.2122 | 0.9479 |
| 0.0957 | 29.0325 | 17145 | 0.2072 | 0.9502 |
### Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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