|
--- |
|
license: cc-by-nc-4.0 |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: videomae-base-finetuned-ucf101-epoch20 |
|
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-ucf101-epoch20 |
|
|
|
This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-NJU/videomae-base) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.8347 |
|
- Accuracy: 0.7704 |
|
|
|
## 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 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_ratio: 0.1 |
|
- training_steps: 79120 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
|
| 1.9278 | 0.05 | 3956 | 2.7016 | 0.3483 | |
|
| 0.6674 | 1.05 | 7912 | 1.5344 | 0.5915 | |
|
| 0.7501 | 2.05 | 11868 | 1.5602 | 0.6477 | |
|
| 0.3266 | 3.05 | 15824 | 1.6153 | 0.6807 | |
|
| 0.6674 | 4.05 | 19780 | 1.5007 | 0.7147 | |
|
| 0.0025 | 5.05 | 23736 | 1.5732 | 0.7065 | |
|
| 0.4971 | 6.05 | 27692 | 1.7131 | 0.7176 | |
|
| 0.0001 | 7.05 | 31648 | 1.5947 | 0.7482 | |
|
| 0.0003 | 8.05 | 35604 | 2.0551 | 0.6958 | |
|
| 0.2192 | 9.05 | 39560 | 1.7950 | 0.7356 | |
|
| 0.1505 | 10.05 | 43516 | 1.9480 | 0.7160 | |
|
| 0.0 | 11.05 | 47472 | 1.5406 | 0.7573 | |
|
| 0.0016 | 12.05 | 51428 | 1.9811 | 0.7207 | |
|
| 0.0005 | 13.05 | 55384 | 1.8196 | 0.7385 | |
|
| 0.0 | 14.05 | 59340 | 1.8393 | 0.7520 | |
|
| 0.0 | 15.05 | 63296 | 1.6738 | 0.7667 | |
|
| 0.0 | 16.05 | 67252 | 1.7355 | 0.7594 | |
|
| 0.0416 | 17.05 | 71208 | 1.7013 | 0.7638 | |
|
| 0.0 | 18.05 | 75164 | 1.6373 | 0.7709 | |
|
| 0.0 | 19.05 | 79120 | 1.5901 | 0.7763 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.30.2 |
|
- Pytorch 2.0.1+cu117 |
|
- Datasets 2.13.1 |
|
- Tokenizers 0.13.3 |
|
|
