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---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base-finetuned-kinetics
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-finetuned-kinetics-finetuned-freeway-subset
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. -->
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/huangyangyu/huggingface/runs/3e8psy1e)
# videomae-base-finetuned-kinetics-finetuned-freeway-subset
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 achieves the following results on the evaluation set:
- Loss: 0.0016
- Accuracy: 1.0
## 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: 5
- eval_batch_size: 5
- 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: 1800
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6551 | 0.02 | 36 | 0.7171 | 0.5 |
| 0.6085 | 1.02 | 72 | 0.7057 | 0.5 |
| 0.5876 | 2.02 | 108 | 0.5834 | 0.75 |
| 0.5757 | 3.02 | 144 | 0.5360 | 0.7143 |
| 0.7017 | 4.02 | 180 | 0.4589 | 0.7143 |
| 0.5681 | 5.02 | 216 | 0.3667 | 0.8214 |
| 0.3418 | 6.02 | 252 | 0.2312 | 0.9286 |
| 0.6408 | 7.02 | 288 | 0.2724 | 0.8929 |
| 0.3846 | 8.02 | 324 | 0.1288 | 0.9643 |
| 0.1551 | 9.02 | 360 | 0.6198 | 0.8214 |
| 0.4879 | 10.02 | 396 | 0.3241 | 0.8571 |
| 0.0982 | 11.02 | 432 | 0.1815 | 0.9286 |
| 0.112 | 12.02 | 468 | 0.2504 | 0.9643 |
| 0.3627 | 13.02 | 504 | 0.2357 | 0.9643 |
| 0.2329 | 14.02 | 540 | 0.6101 | 0.8571 |
| 0.141 | 15.02 | 576 | 0.0218 | 1.0 |
| 0.1755 | 16.02 | 612 | 0.0791 | 0.9643 |
| 0.079 | 17.02 | 648 | 0.1167 | 0.9643 |
| 0.0859 | 18.02 | 684 | 0.0118 | 1.0 |
| 0.0131 | 19.02 | 720 | 0.0020 | 1.0 |
| 0.0014 | 20.02 | 756 | 0.0054 | 1.0 |
| 0.0008 | 21.02 | 792 | 0.0841 | 0.9286 |
| 0.0024 | 22.02 | 828 | 0.0852 | 0.9643 |
| 0.1803 | 23.02 | 864 | 0.0005 | 1.0 |
| 0.0001 | 24.02 | 900 | 0.0379 | 0.9643 |
| 0.0012 | 25.02 | 936 | 0.0705 | 0.9643 |
| 0.0018 | 26.02 | 972 | 0.0010 | 1.0 |
| 0.0007 | 27.02 | 1008 | 0.0210 | 1.0 |
| 0.0028 | 28.02 | 1044 | 0.0030 | 1.0 |
| 0.0465 | 29.02 | 1080 | 0.0005 | 1.0 |
| 0.0004 | 30.02 | 1116 | 0.0011 | 1.0 |
| 0.0016 | 31.02 | 1152 | 0.0005 | 1.0 |
| 0.0 | 32.02 | 1188 | 0.0012 | 1.0 |
| 0.0002 | 33.02 | 1224 | 0.0001 | 1.0 |
| 0.0315 | 34.02 | 1260 | 0.0027 | 1.0 |
| 0.0253 | 35.02 | 1296 | 0.0003 | 1.0 |
| 0.0011 | 36.02 | 1332 | 0.0022 | 1.0 |
| 0.0001 | 37.02 | 1368 | 0.0006 | 1.0 |
| 0.0007 | 38.02 | 1404 | 0.0120 | 1.0 |
| 0.0001 | 39.02 | 1440 | 0.1001 | 0.9643 |
| 0.0005 | 40.02 | 1476 | 0.0331 | 0.9643 |
| 0.0009 | 41.02 | 1512 | 0.0418 | 0.9643 |
| 0.0035 | 42.02 | 1548 | 0.0761 | 0.9643 |
| 0.0001 | 43.02 | 1584 | 0.0020 | 1.0 |
| 0.0001 | 44.02 | 1620 | 0.0020 | 1.0 |
| 0.0 | 45.02 | 1656 | 0.0010 | 1.0 |
| 0.0001 | 46.02 | 1692 | 0.0009 | 1.0 |
| 0.0005 | 47.02 | 1728 | 0.0012 | 1.0 |
| 0.0001 | 48.02 | 1764 | 0.0015 | 1.0 |
| 0.0002 | 49.02 | 1800 | 0.0016 | 1.0 |
### Framework versions
- Transformers 4.42.0.dev0
- Pytorch 2.1.1
- Datasets 2.19.2
- Tokenizers 0.19.1
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