|
--- |
|
license: cc-by-nc-4.0 |
|
base_model: abduldattijo/videomae-base-finetuned-ucf101-subset |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: videomae-base-finetuned-ucf101-subset-V3KILLER |
|
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-ucf101-subset-V3KILLER |
|
|
|
This model is a fine-tuned version of [abduldattijo/videomae-base-finetuned-ucf101-subset](https://huggingface.co./abduldattijo/videomae-base-finetuned-ucf101-subset) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.2181 |
|
- Accuracy: 0.9615 |
|
|
|
## 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: 5960 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 0.3447 | 0.03 | 150 | 0.1339 | 0.9579 | |
|
| 0.3161 | 1.03 | 300 | 0.1538 | 0.9465 | |
|
| 0.3386 | 2.03 | 450 | 0.3260 | 0.9019 | |
|
| 0.3572 | 3.03 | 600 | 0.1967 | 0.9311 | |
|
| 0.3699 | 4.03 | 750 | 0.1661 | 0.9505 | |
|
| 0.3125 | 5.03 | 900 | 0.3292 | 0.9205 | |
|
| 0.4785 | 6.03 | 1050 | 0.2029 | 0.9324 | |
|
| 0.3477 | 7.03 | 1200 | 0.1534 | 0.9385 | |
|
| 0.2909 | 8.03 | 1350 | 0.1265 | 0.9571 | |
|
| 0.2646 | 9.03 | 1500 | 0.1239 | 0.9586 | |
|
| 0.3339 | 10.03 | 1650 | 0.1341 | 0.9628 | |
|
| 0.0954 | 11.03 | 1800 | 0.1835 | 0.9423 | |
|
| 0.3861 | 12.03 | 1950 | 0.2241 | 0.9467 | |
|
| 0.248 | 13.03 | 2100 | 0.1258 | 0.9620 | |
|
| 0.2513 | 14.03 | 2250 | 0.2217 | 0.9357 | |
|
| 0.1133 | 15.03 | 2400 | 0.2129 | 0.9406 | |
|
| 0.1421 | 16.03 | 2550 | 0.3006 | 0.9264 | |
|
| 0.0248 | 17.03 | 2700 | 0.3868 | 0.9142 | |
|
| 0.0166 | 18.03 | 2850 | 0.2594 | 0.9518 | |
|
| 0.0874 | 19.03 | 3000 | 0.3652 | 0.9252 | |
|
| 0.0889 | 20.03 | 3150 | 0.2249 | 0.9533 | |
|
| 0.0804 | 21.03 | 3300 | 0.2027 | 0.9628 | |
|
| 0.0019 | 22.03 | 3450 | 0.4682 | 0.9212 | |
|
| 0.0405 | 23.03 | 3600 | 0.2425 | 0.9493 | |
|
| 0.0847 | 24.03 | 3750 | 0.2456 | 0.9558 | |
|
| 0.1656 | 25.03 | 3900 | 0.2623 | 0.9505 | |
|
| 0.1007 | 26.03 | 4050 | 0.2389 | 0.9484 | |
|
| 0.0616 | 27.03 | 4200 | 0.2529 | 0.9543 | |
|
| 0.0005 | 28.03 | 4350 | 0.1521 | 0.9732 | |
|
| 0.0006 | 29.03 | 4500 | 0.4115 | 0.9165 | |
|
| 0.0007 | 30.03 | 4650 | 0.4279 | 0.9220 | |
|
| 0.0004 | 31.03 | 4800 | 0.3572 | 0.9372 | |
|
| 0.0003 | 32.03 | 4950 | 0.3314 | 0.9419 | |
|
| 0.0002 | 33.03 | 5100 | 0.4008 | 0.9347 | |
|
| 0.0611 | 34.03 | 5250 | 0.4632 | 0.9239 | |
|
| 0.0003 | 35.03 | 5400 | 0.3756 | 0.9368 | |
|
| 0.0003 | 36.03 | 5550 | 0.3745 | 0.9429 | |
|
| 0.163 | 37.03 | 5700 | 0.3967 | 0.9383 | |
|
| 0.0059 | 38.03 | 5850 | 0.3808 | 0.9389 | |
|
| 0.0003 | 39.02 | 5960 | 0.3824 | 0.9395 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.35.2 |
|
- Pytorch 2.1.1+cu118 |
|
- Datasets 2.15.0 |
|
- Tokenizers 0.15.0 |
|
|
