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---
library_name: transformers
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-allkisa-crop-background-0312-clip_duration-abnormal12_resize
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-kinetics-allkisa-crop-background-0312-clip_duration-abnormal12_resize
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: 0.3122
- Accuracy: 0.9393
## 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: 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: 0.05
- training_steps: 29600
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.6616 | 0.01 | 296 | 0.3786 | 0.8675 |
| 0.1816 | 1.01 | 592 | 0.5763 | 0.8352 |
| 0.0266 | 2.01 | 888 | 0.6628 | 0.8078 |
| 0.4168 | 3.01 | 1184 | 0.4009 | 0.8562 |
| 0.0271 | 4.01 | 1480 | 0.4466 | 0.8675 |
| 0.4371 | 5.01 | 1776 | 0.5005 | 0.8498 |
| 0.0269 | 6.01 | 2072 | 0.5684 | 0.8498 |
| 0.0061 | 7.01 | 2368 | 0.5858 | 0.8643 |
| 0.0262 | 8.01 | 2664 | 0.4571 | 0.8901 |
| 0.0003 | 9.01 | 2960 | 0.6348 | 0.8627 |
| 0.0004 | 10.01 | 3256 | 0.6531 | 0.8708 |
| 0.002 | 11.01 | 3552 | 0.5016 | 0.8821 |
| 0.0048 | 12.01 | 3848 | 0.6594 | 0.8578 |
| 0.5788 | 13.01 | 4144 | 0.5558 | 0.8934 |
| 0.0002 | 14.01 | 4440 | 0.6740 | 0.8611 |
| 0.0001 | 15.01 | 4736 | 0.5346 | 0.8950 |
| 0.007 | 16.01 | 5032 | 0.6110 | 0.8885 |
| 0.0001 | 17.01 | 5328 | 0.6141 | 0.8869 |
| 0.0363 | 18.01 | 5624 | 0.5504 | 0.8934 |
| 0.0002 | 19.01 | 5920 | 0.5372 | 0.8982 |
| 0.4009 | 20.01 | 6216 | 0.5422 | 0.8998 |
| 0.0049 | 21.01 | 6512 | 0.5687 | 0.8918 |
| 0.0048 | 22.01 | 6808 | 0.5355 | 0.8982 |
| 0.0 | 23.01 | 7104 | 0.5720 | 0.8982 |
| 0.0038 | 24.01 | 7400 | 0.5421 | 0.9047 |
| 0.0004 | 25.01 | 7696 | 0.6254 | 0.8950 |
| 0.0002 | 26.01 | 7992 | 0.5809 | 0.8998 |
| 0.0031 | 27.01 | 8288 | 0.5869 | 0.8966 |
| 0.0011 | 28.01 | 8584 | 0.6073 | 0.8950 |
| 0.0001 | 29.01 | 8880 | 0.5942 | 0.9015 |
| 0.5734 | 30.01 | 9176 | 0.5724 | 0.8998 |
| 0.0001 | 31.01 | 9472 | 0.5558 | 0.9047 |
| 0.0001 | 32.01 | 9768 | 0.5694 | 0.8982 |
| 0.0 | 33.01 | 10064 | 0.5874 | 0.9031 |
| 0.0 | 34.01 | 10360 | 0.6037 | 0.8966 |
### Framework versions
- Transformers 4.48.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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