|
--- |
|
license: cc-by-nc-4.0 |
|
base_model: MCG-NJU/videomae-base |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: videomae-base-finetuned-SLT-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. --> |
|
|
|
# videomae-base-finetuned-SLT-subset |
|
|
|
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: 0.1513 |
|
- 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: 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: 944 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 3.9224 | 0.06 | 59 | 3.7150 | 0.025 | |
|
| 3.9538 | 1.06 | 118 | 3.7131 | 0.025 | |
|
| 3.8824 | 2.06 | 177 | 3.6952 | 0.025 | |
|
| 3.8135 | 3.06 | 236 | 3.6851 | 0.05 | |
|
| 3.8444 | 4.06 | 295 | 3.6689 | 0.025 | |
|
| 3.7715 | 5.06 | 354 | 3.6183 | 0.05 | |
|
| 3.6616 | 6.06 | 413 | 3.4405 | 0.4 | |
|
| 3.6175 | 7.06 | 472 | 3.0778 | 0.325 | |
|
| 3.1062 | 8.06 | 531 | 2.0972 | 0.75 | |
|
| 1.8942 | 9.06 | 590 | 1.2638 | 0.925 | |
|
| 1.3975 | 10.06 | 649 | 0.7811 | 0.975 | |
|
| 1.0269 | 11.06 | 708 | 0.4473 | 1.0 | |
|
| 0.3623 | 12.06 | 767 | 0.3073 | 1.0 | |
|
| 0.3611 | 13.06 | 826 | 0.2007 | 1.0 | |
|
| 0.1881 | 14.06 | 885 | 0.1614 | 1.0 | |
|
| 0.1773 | 15.06 | 944 | 0.1513 | 1.0 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.33.3 |
|
- Pytorch 2.0.1+cu118 |
|
- Datasets 2.14.5 |
|
- Tokenizers 0.13.3 |
|
|
