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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: CTMAE2_CS_V7_9
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. -->
# CTMAE2_CS_V7_9
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: 1.0853
- 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: 5
- eval_batch_size: 5
- 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: 7750
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.6691 | 0.0201 | 156 | 0.7815 | 0.4667 |
| 0.6103 | 1.0201 | 312 | 0.8786 | 0.4667 |
| 0.5756 | 2.0201 | 468 | 0.9522 | 0.4667 |
| 0.5278 | 3.0201 | 624 | 0.7274 | 0.5556 |
| 0.4309 | 4.0201 | 780 | 0.8362 | 0.6 |
| 0.4808 | 5.0201 | 936 | 0.8308 | 0.5333 |
| 0.373 | 6.0201 | 1092 | 0.6670 | 0.5778 |
| 0.8291 | 7.0201 | 1248 | 0.5672 | 0.7333 |
| 0.5016 | 8.0201 | 1404 | 0.5802 | 0.7111 |
| 0.2954 | 9.0201 | 1560 | 0.8878 | 0.6222 |
| 0.2576 | 10.0201 | 1716 | 0.5753 | 0.7778 |
| 0.4279 | 11.0201 | 1872 | 0.9186 | 0.6889 |
| 0.2818 | 12.0201 | 2028 | 1.3718 | 0.6 |
| 0.4623 | 13.0201 | 2184 | 1.2370 | 0.7111 |
| 0.3438 | 14.0201 | 2340 | 1.6716 | 0.5778 |
| 0.4862 | 15.0201 | 2496 | 0.9000 | 0.7778 |
| 0.2198 | 16.0201 | 2652 | 1.2056 | 0.6667 |
| 0.1955 | 17.0201 | 2808 | 1.0853 | 0.8 |
| 0.2232 | 18.0201 | 2964 | 2.0170 | 0.6444 |
| 0.6413 | 19.0201 | 3120 | 1.3823 | 0.7111 |
| 0.3481 | 20.0201 | 3276 | 0.9786 | 0.7111 |
| 0.1043 | 21.0201 | 3432 | 1.3672 | 0.7778 |
| 0.3651 | 22.0201 | 3588 | 1.5295 | 0.6444 |
| 0.1562 | 23.0201 | 3744 | 1.0870 | 0.7778 |
| 0.137 | 24.0201 | 3900 | 1.9200 | 0.6889 |
| 0.446 | 25.0201 | 4056 | 1.9016 | 0.6667 |
| 0.0023 | 26.0201 | 4212 | 1.6282 | 0.7333 |
| 0.3529 | 27.0201 | 4368 | 1.7609 | 0.6444 |
| 0.384 | 28.0201 | 4524 | 1.6187 | 0.7333 |
| 0.2808 | 29.0201 | 4680 | 2.1017 | 0.6 |
| 0.1582 | 30.0201 | 4836 | 1.7994 | 0.7333 |
| 0.1092 | 31.0201 | 4992 | 1.3328 | 0.7556 |
| 0.2964 | 32.0201 | 5148 | 2.8201 | 0.5778 |
| 0.2952 | 33.0201 | 5304 | 1.4045 | 0.7778 |
| 0.3124 | 34.0201 | 5460 | 1.6641 | 0.7111 |
| 0.0011 | 35.0201 | 5616 | 1.7113 | 0.7111 |
| 0.1375 | 36.0201 | 5772 | 2.0553 | 0.6667 |
| 0.1252 | 37.0201 | 5928 | 2.2712 | 0.6444 |
| 0.1576 | 38.0201 | 6084 | 2.0950 | 0.6889 |
| 0.0008 | 39.0201 | 6240 | 2.9621 | 0.6 |
| 0.0003 | 40.0201 | 6396 | 1.9269 | 0.7333 |
| 0.0002 | 41.0201 | 6552 | 2.2481 | 0.6889 |
| 0.0111 | 42.0201 | 6708 | 2.1604 | 0.6667 |
| 0.3096 | 43.0201 | 6864 | 2.9864 | 0.6 |
| 0.0006 | 44.0201 | 7020 | 2.0592 | 0.7111 |
| 0.0001 | 45.0201 | 7176 | 2.2161 | 0.7111 |
| 0.0002 | 46.0201 | 7332 | 2.2129 | 0.7111 |
| 0.0002 | 47.0201 | 7488 | 2.3814 | 0.6889 |
| 0.0001 | 48.0201 | 7644 | 2.2948 | 0.7111 |
| 0.2534 | 49.0137 | 7750 | 2.3587 | 0.6889 |
### Framework versions
- Transformers 4.46.2
- Pytorch 2.0.1+cu117
- Datasets 3.0.1
- Tokenizers 0.20.0
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