|
--- |
|
license: cc-by-nc-4.0 |
|
base_model: facebook/timesformer-base-finetuned-k400 |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
- f1 |
|
model-index: |
|
- name: videomae-surf-analytics-runpod |
|
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-surf-analytics-runpod |
|
|
|
This model is a fine-tuned version of [facebook/timesformer-base-finetuned-k400](https://huggingface.co/facebook/timesformer-base-finetuned-k400) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.4027 |
|
- Accuracy: 0.8838 |
|
- F1: 0.8838 |
|
|
|
## 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: 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: 610 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
|
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:| |
|
| 0.6712 | 0.1016 | 62 | 0.8671 | 0.6680 | 0.6623 | |
|
| 0.3119 | 1.1016 | 124 | 0.5911 | 0.7884 | 0.7887 | |
|
| 0.2505 | 2.1016 | 186 | 0.5297 | 0.8008 | 0.8002 | |
|
| 0.207 | 3.1016 | 248 | 0.5970 | 0.7801 | 0.7787 | |
|
| 0.1743 | 4.1016 | 310 | 0.5612 | 0.8050 | 0.7984 | |
|
| 0.1005 | 5.1016 | 372 | 0.4027 | 0.8838 | 0.8838 | |
|
| 0.0147 | 6.1016 | 434 | 0.4360 | 0.8589 | 0.8573 | |
|
| 0.0573 | 7.1016 | 496 | 0.4451 | 0.8714 | 0.8697 | |
|
| 0.0143 | 8.1016 | 558 | 0.4099 | 0.8672 | 0.8666 | |
|
| 0.1311 | 9.0852 | 610 | 0.4056 | 0.8755 | 0.8752 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.41.2 |
|
- Pytorch 2.3.1+cu121 |
|
- Datasets 2.19.2 |
|
- Tokenizers 0.19.1 |
|
|