|
--- |
|
license: cc-by-nc-4.0 |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: videomae-base-finetuned-kinetics-finetuned-rwf2000mp4-epochs8-batch8-kb |
|
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-finetuned-rwf2000mp4-epochs8-batch8-kb |
|
|
|
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: 0.8559 |
|
- Accuracy: 0.7453 |
|
|
|
## 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: 2 |
|
- eval_batch_size: 2 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 8 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_ratio: 0.1 |
|
- training_steps: 3200 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 0.3514 | 0.06 | 200 | 0.2837 | 0.8875 | |
|
| 0.3156 | 1.06 | 400 | 0.6930 | 0.7625 | |
|
| 0.2273 | 2.06 | 600 | 0.5692 | 0.805 | |
|
| 0.2091 | 3.06 | 800 | 0.3872 | 0.8612 | |
|
| 0.1875 | 4.06 | 1000 | 0.3394 | 0.8725 | |
|
| 0.1206 | 5.06 | 1200 | 0.4416 | 0.8562 | |
|
| 0.1302 | 6.06 | 1400 | 1.0851 | 0.7475 | |
|
| 0.3417 | 7.06 | 1600 | 0.5024 | 0.8638 | |
|
| 0.2545 | 8.06 | 1800 | 0.3819 | 0.9 | |
|
| 0.1787 | 9.06 | 2000 | 0.3864 | 0.8962 | |
|
| 0.0761 | 10.06 | 2200 | 0.5604 | 0.8562 | |
|
| 0.076 | 11.06 | 2400 | 0.5780 | 0.8725 | |
|
| 0.1476 | 12.06 | 2600 | 0.5479 | 0.8725 | |
|
| 0.1274 | 13.06 | 2800 | 0.5843 | 0.87 | |
|
| 0.0382 | 14.06 | 3000 | 0.6739 | 0.8525 | |
|
| 0.0143 | 15.06 | 3200 | 0.5568 | 0.8738 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.25.1 |
|
- Pytorch 1.13.1+cu117 |
|
- Datasets 2.8.0 |
|
- Tokenizers 0.13.2 |
|
|
