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---
library_name: transformers
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-large-finetuned-kinetics
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: CTMAE-P2-V3-3G-S2
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. -->
# CTMAE-P2-V3-3G-S2
This model is a fine-tuned version of [MCG-NJU/videomae-large-finetuned-kinetics](https://huggingface.co/MCG-NJU/videomae-large-finetuned-kinetics) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9771
- Accuracy: 0.8
## 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: 1e-05
- train_batch_size: 4
- eval_batch_size: 4
- 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: 3250
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.6262 | 0.0203 | 66 | 0.8422 | 0.4 |
| 0.5961 | 1.0203 | 132 | 0.9177 | 0.4 |
| 0.6691 | 2.0203 | 198 | 0.8617 | 0.4 |
| 0.6242 | 3.0203 | 264 | 0.9506 | 0.4 |
| 0.631 | 4.0203 | 330 | 0.7678 | 0.4 |
| 0.6747 | 5.0203 | 396 | 0.6632 | 0.6 |
| 0.6345 | 6.0203 | 462 | 0.7091 | 0.5556 |
| 0.6357 | 7.0203 | 528 | 1.0969 | 0.5111 |
| 0.4717 | 8.0203 | 594 | 0.6719 | 0.6444 |
| 0.827 | 9.0203 | 660 | 0.5489 | 0.7778 |
| 0.3107 | 10.0203 | 726 | 0.7150 | 0.6889 |
| 0.3366 | 11.0203 | 792 | 0.7248 | 0.7111 |
| 0.8919 | 12.0203 | 858 | 0.6667 | 0.7778 |
| 0.4823 | 13.0203 | 924 | 2.1050 | 0.4222 |
| 0.3742 | 14.0203 | 990 | 1.0017 | 0.5778 |
| 0.3399 | 15.0203 | 1056 | 1.5679 | 0.5556 |
| 0.6571 | 16.0203 | 1122 | 1.3521 | 0.6 |
| 0.2434 | 17.0203 | 1188 | 0.7812 | 0.7778 |
| 0.5967 | 18.0203 | 1254 | 0.9575 | 0.6889 |
| 0.1982 | 19.0203 | 1320 | 1.1721 | 0.6667 |
| 0.2631 | 20.0203 | 1386 | 2.5733 | 0.4667 |
| 0.3235 | 21.0203 | 1452 | 0.9771 | 0.8 |
| 0.1786 | 22.0203 | 1518 | 1.1978 | 0.7111 |
| 0.1352 | 23.0203 | 1584 | 0.8692 | 0.7778 |
| 0.1709 | 24.0203 | 1650 | 1.1424 | 0.7556 |
| 0.0873 | 25.0203 | 1716 | 1.8760 | 0.6222 |
| 0.1418 | 26.0203 | 1782 | 1.0964 | 0.8 |
| 0.0075 | 27.0203 | 1848 | 1.9130 | 0.6222 |
| 0.4534 | 28.0203 | 1914 | 1.1176 | 0.7778 |
| 0.0019 | 29.0203 | 1980 | 2.0684 | 0.6222 |
| 0.4098 | 30.0203 | 2046 | 1.9198 | 0.6667 |
| 0.0006 | 31.0203 | 2112 | 1.2724 | 0.7333 |
| 0.1891 | 32.0203 | 2178 | 1.8213 | 0.6444 |
| 0.0604 | 33.0203 | 2244 | 2.6845 | 0.5556 |
| 0.104 | 34.0203 | 2310 | 2.7468 | 0.6222 |
| 0.028 | 35.0203 | 2376 | 1.4458 | 0.7333 |
| 0.2479 | 36.0203 | 2442 | 2.1613 | 0.6222 |
| 0.0967 | 37.0203 | 2508 | 1.3895 | 0.7778 |
| 0.0668 | 38.0203 | 2574 | 2.0147 | 0.6667 |
| 0.0004 | 39.0203 | 2640 | 1.5766 | 0.6889 |
| 0.0027 | 40.0203 | 2706 | 2.3533 | 0.6444 |
| 0.1436 | 41.0203 | 2772 | 2.1496 | 0.6444 |
| 0.0327 | 42.0203 | 2838 | 2.2866 | 0.6444 |
| 0.0349 | 43.0203 | 2904 | 2.2496 | 0.6667 |
| 0.1178 | 44.0203 | 2970 | 1.8929 | 0.6889 |
| 0.0001 | 45.0203 | 3036 | 1.9030 | 0.7111 |
| 0.1289 | 46.0203 | 3102 | 1.9212 | 0.6889 |
| 0.137 | 47.0203 | 3168 | 1.6077 | 0.7556 |
| 0.0004 | 48.0203 | 3234 | 1.7398 | 0.7333 |
| 0.0001 | 49.0049 | 3250 | 1.7423 | 0.7333 |
### Framework versions
- Transformers 4.46.2
- Pytorch 2.0.1+cu117
- Datasets 3.0.1
- Tokenizers 0.20.0
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