|
--- |
|
license: cc-by-nc-4.0 |
|
base_model: MCG-NJU/videomae-base-finetuned-kinetics |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
- precision |
|
- recall |
|
model-index: |
|
- name: videomae-base-finetuned-kinetics-fight_18-03-2024 |
|
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-fight_18-03-2024 |
|
|
|
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: 0.2211 |
|
- Accuracy: 0.9175 |
|
- Precision: 0.9372 |
|
- Recall: 0.895 |
|
|
|
## 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-07 |
|
- train_batch_size: 12 |
|
- eval_batch_size: 12 |
|
- 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: 2660 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:| |
|
| 0.7318 | 0.05 | 134 | 0.7169 | 0.43 | 0.4247 | 0.395 | |
|
| 0.6646 | 1.05 | 268 | 0.6636 | 0.59 | 0.6139 | 0.485 | |
|
| 0.6089 | 2.05 | 402 | 0.5944 | 0.78 | 0.8415 | 0.69 | |
|
| 0.5485 | 3.05 | 536 | 0.5270 | 0.845 | 0.8920 | 0.785 | |
|
| 0.4581 | 4.05 | 670 | 0.4630 | 0.865 | 0.9011 | 0.82 | |
|
| 0.3436 | 5.05 | 804 | 0.3994 | 0.8725 | 0.9162 | 0.82 | |
|
| 0.3109 | 6.05 | 938 | 0.3530 | 0.8775 | 0.9171 | 0.83 | |
|
| 0.2672 | 7.05 | 1072 | 0.3212 | 0.88 | 0.9176 | 0.835 | |
|
| 0.2243 | 8.05 | 1206 | 0.2947 | 0.895 | 0.9202 | 0.865 | |
|
| 0.297 | 9.05 | 1340 | 0.2779 | 0.895 | 0.9202 | 0.865 | |
|
| 0.21 | 10.05 | 1474 | 0.2615 | 0.9025 | 0.9215 | 0.88 | |
|
| 0.2003 | 11.05 | 1608 | 0.2515 | 0.895 | 0.9202 | 0.865 | |
|
| 0.2128 | 12.05 | 1742 | 0.2418 | 0.91 | 0.9271 | 0.89 | |
|
| 0.1789 | 13.05 | 1876 | 0.2357 | 0.9125 | 0.9275 | 0.895 | |
|
| 0.1672 | 14.05 | 2010 | 0.2300 | 0.91 | 0.9227 | 0.895 | |
|
| 0.1532 | 15.05 | 2144 | 0.2275 | 0.9175 | 0.9372 | 0.895 | |
|
| 0.1695 | 16.05 | 2278 | 0.2241 | 0.9125 | 0.9275 | 0.895 | |
|
| 0.1255 | 17.05 | 2412 | 0.2225 | 0.915 | 0.9323 | 0.895 | |
|
| 0.1168 | 18.05 | 2546 | 0.2214 | 0.9175 | 0.9372 | 0.895 | |
|
| 0.1395 | 19.04 | 2660 | 0.2211 | 0.9175 | 0.9372 | 0.895 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.38.2 |
|
- Pytorch 2.0.1+cu118 |
|
- Datasets 2.18.0 |
|
- Tokenizers 0.15.2 |
|
|
