đ videomae-base-finetuned-kinetics-0409_final_5sec_org_ab7_val_inside_train
This model is a fine - tuned version of [MCG - NJU/videomae - base - finetuned - kinetics](https://huggingface.co/MCG - NJU/videomae - base - finetuned - kinetics) on an unknown dataset. It offers high - performance video analysis capabilities with remarkable accuracy on the evaluation set.
đ Quick Start
This model has achieved the following results on the evaluation set:
- Loss: 0.3255
- Accuracy: 0.9138
đ Documentation
Model Information
| Property |
Details |
| Library Name |
transformers |
| Model Type |
videomae - base - finetuned - kinetics - 0409_final_5sec_org_ab7_val_inside_train |
| Base Model |
MCG - NJU/videomae - base - finetuned - kinetics |
| Tags |
generated_from_trainer |
| Metrics |
accuracy |
| License |
cc - by - nc - 4.0 |
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: 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: 0.05
- training_steps: 67100
Training Results
| Training Loss |
Epoch |
Step |
Validation Loss |
Accuracy |
| 0.4404 |
0.0100 |
672 |
0.2641 |
0.8958 |
| 0.0506 |
1.0100 |
1344 |
0.2971 |
0.9045 |
| 0.0077 |
2.0100 |
2016 |
0.8203 |
0.8293 |
| 0.016 |
3.0100 |
2688 |
0.4447 |
0.8958 |
| 0.0012 |
4.0100 |
3360 |
0.5228 |
0.8622 |
| 0.0003 |
5.0100 |
4032 |
0.5333 |
0.8731 |
| 0.0019 |
6.0100 |
4704 |
0.5615 |
0.8786 |
| 0.0669 |
7.0100 |
5376 |
0.3206 |
0.9162 |
| 0.0056 |
8.0100 |
6048 |
0.5627 |
0.8849 |
| 0.0003 |
9.0100 |
6720 |
0.6655 |
0.8567 |
| 0.0063 |
10.0100 |
7392 |
0.6566 |
0.8786 |
| 0.0003 |
11.0100 |
8064 |
0.5058 |
0.8778 |
| 0.0005 |
12.0100 |
8736 |
0.4329 |
0.9045 |
| 0.0005 |
13.0100 |
9408 |
0.4837 |
0.8943 |
| 0.0182 |
14.0100 |
10080 |
0.6702 |
0.8692 |
| 0.0001 |
15.0100 |
10752 |
0.7277 |
0.8583 |
| 0.0001 |
16.0100 |
11424 |
0.6110 |
0.8763 |
| 0.0001 |
17.0100 |
12096 |
0.5027 |
0.9146 |
| 0.0006 |
18.0100 |
12768 |
0.4604 |
0.9068 |
| 0.0138 |
19.0100 |
13440 |
0.4703 |
0.9123 |
| 0.0 |
20.0100 |
14112 |
0.4712 |
0.9068 |
| 0.5385 |
21.0100 |
14784 |
0.5793 |
0.9021 |
| 0.0001 |
22.0100 |
15456 |
0.4995 |
0.9162 |
Framework Versions
- Transformers 4.48.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
đ License
This model is released under the cc - by - nc - 4.0 license.
%20--%3e%3cdefs%3e%3cstyle%3e%20.st0%20{%20fill:%20%23061b40;%20}%20.st1%20{%20fill:%20%23306af1;%20}%20.st2%20{%20fill:%20%235ce5cf;%20}%20%3c/style%3e%3c/defs%3e%3cg%3e%3cpath%20class='st0'%20d='M55,10.5h9v3h-9v9h12V7.5h-12v3ZM64,19.5h-6v-3h6v3Z'/%3e%3cpolygon%20class='st0'%20points='69%2016.5%2078%2016.5%2078%2019.5%2069%2019.5%2069%2022.5%2081%2022.5%2081%2013.5%2072%2013.5%2072%2010.5%2081%2010.5%2081%207.5%2069%207.5%2069%2016.5'/%3e%3cpolygon%20class='st0'%20points='95%2010.5%2095%207.5%2083%207.5%2083%2022.5%2095%2022.5%2095%2019.5%2086%2019.5%2086%2016.5%2095%2016.5%2095%2013.5%2086%2013.5%2086%2010.5%2095%2010.5'/%3e%3cpath%20class='st0'%20d='M40,1.5v21h11.6l1.4-1.4v-7.6h0c0,0-1.4-1.5-1.4-1.5l1.4-1.4V2.9l-1.4-1.4h-11.6ZM50,19.5h-7v-6h7v6ZM50,10.5h-7v-6h7v6Z'/%3e%3c/g%3e%3cpath%20class='st1'%20d='M23.1,24L14.7,4.8l-4.9,11.2h3.8l-1.8,4H3.3L12.1,0H2C.9,0,0,.9,0,2v20c0,1.1.9,2,2,2h21.1Z'/%3e%3cpath%20class='st2'%20d='M34,0h-16.8l10.6,24h6.2c1.1,0,2-.9,2-2V2C36,.9,35.1,0,34,0ZM32.5,20h-4V4h4v16Z'/%3e%3c/svg%3e)
