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---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base-short-ssv2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-short-ssv2-finetuned-ct_cpc
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-short-ssv2-finetuned-ct_cpc
This model is a fine-tuned version of [MCG-NJU/videomae-base-short-ssv2](https://huggingface.co/MCG-NJU/videomae-base-short-ssv2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1547
- Accuracy: 0.6508
## 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: 6
- eval_batch_size: 6
- 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: 2300
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4832 | 0.02 | 47 | 1.1203 | 0.6667 |
| 1.32 | 1.02 | 94 | 1.0505 | 0.6667 |
| 1.1539 | 2.02 | 141 | 1.0525 | 0.6667 |
| 1.2399 | 3.02 | 188 | 1.0354 | 0.6667 |
| 0.9928 | 4.02 | 235 | 1.0516 | 0.6667 |
| 1.0054 | 5.02 | 282 | 1.0297 | 0.6667 |
| 1.1166 | 6.02 | 329 | 1.0247 | 0.6667 |
| 1.2715 | 7.02 | 376 | 1.0098 | 0.6667 |
| 1.0317 | 8.02 | 423 | 1.0404 | 0.6667 |
| 1.1258 | 9.02 | 470 | 1.0054 | 0.6667 |
| 0.8991 | 10.02 | 517 | 1.0477 | 0.6667 |
| 0.8957 | 11.02 | 564 | 1.0608 | 0.6667 |
| 1.078 | 12.02 | 611 | 1.0166 | 0.6667 |
| 0.9067 | 13.02 | 658 | 1.2110 | 0.6667 |
| 1.0383 | 14.02 | 705 | 1.0380 | 0.6 |
| 1.2244 | 15.02 | 752 | 1.1041 | 0.6667 |
| 1.0364 | 16.02 | 799 | 1.0123 | 0.6 |
| 0.9662 | 17.02 | 846 | 1.1803 | 0.6333 |
| 0.9299 | 18.02 | 893 | 1.0910 | 0.6333 |
| 0.877 | 19.02 | 940 | 1.0183 | 0.65 |
| 0.8649 | 20.02 | 987 | 1.1415 | 0.6167 |
| 0.8841 | 21.02 | 1034 | 1.0975 | 0.6333 |
| 0.6276 | 22.02 | 1081 | 1.0728 | 0.6 |
| 0.7974 | 23.02 | 1128 | 1.1676 | 0.5833 |
| 0.7381 | 24.02 | 1175 | 1.1624 | 0.55 |
| 0.4807 | 25.02 | 1222 | 1.1930 | 0.55 |
| 0.6812 | 26.02 | 1269 | 1.1511 | 0.6 |
| 0.5802 | 27.02 | 1316 | 1.2315 | 0.6167 |
| 0.5943 | 28.02 | 1363 | 1.1641 | 0.5667 |
| 0.5416 | 29.02 | 1410 | 1.0963 | 0.6 |
| 0.6676 | 30.02 | 1457 | 1.1131 | 0.5667 |
| 0.4085 | 31.02 | 1504 | 1.2948 | 0.5833 |
| 0.4548 | 32.02 | 1551 | 1.2788 | 0.6333 |
| 0.4351 | 33.02 | 1598 | 1.1922 | 0.5667 |
| 0.5641 | 34.02 | 1645 | 1.2677 | 0.55 |
| 0.4471 | 35.02 | 1692 | 1.2766 | 0.6167 |
| 0.361 | 36.02 | 1739 | 1.2525 | 0.55 |
| 0.5668 | 37.02 | 1786 | 1.2928 | 0.55 |
| 0.5262 | 38.02 | 1833 | 1.2429 | 0.6333 |
| 0.4901 | 39.02 | 1880 | 1.1457 | 0.5667 |
| 0.481 | 40.02 | 1927 | 1.2137 | 0.5833 |
| 0.3566 | 41.02 | 1974 | 1.1830 | 0.6167 |
| 0.5147 | 42.02 | 2021 | 1.1629 | 0.6 |
| 0.4013 | 43.02 | 2068 | 1.2735 | 0.6 |
| 0.3895 | 44.02 | 2115 | 1.2758 | 0.6167 |
| 0.3727 | 45.02 | 2162 | 1.2519 | 0.5833 |
| 0.2379 | 46.02 | 2209 | 1.2318 | 0.5833 |
| 0.2985 | 47.02 | 2256 | 1.2594 | 0.5833 |
| 0.2991 | 48.02 | 2300 | 1.2510 | 0.5833 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.0.1+cu117
- Datasets 3.0.1
- Tokenizers 0.15.1
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