|
--- |
|
library_name: transformers |
|
license: cc-by-nc-4.0 |
|
base_model: MCG-NJU/videomae-base |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: videomae-base-finetuned-ucf101-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-ucf101-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: 0.5126 |
|
- Accuracy: 0.7586 |
|
|
|
## 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: 16 |
|
- eval_batch_size: 16 |
|
- 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: 150 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-------:|:----:|:---------------:|:--------:| |
|
| 0.9276 | 0.0933 | 14 | 0.8787 | 0.6207 | |
|
| 0.8845 | 1.0933 | 28 | 0.7380 | 0.7069 | |
|
| 0.685 | 2.0933 | 42 | 0.7084 | 0.7069 | |
|
| 0.7556 | 3.0933 | 56 | 0.6161 | 0.8103 | |
|
| 0.5482 | 4.0933 | 70 | 0.6827 | 0.7414 | |
|
| 0.6461 | 5.0933 | 84 | 0.6916 | 0.7069 | |
|
| 0.701 | 6.0933 | 98 | 0.5490 | 0.8103 | |
|
| 0.5242 | 7.0933 | 112 | 0.5372 | 0.7931 | |
|
| 0.4482 | 8.0933 | 126 | 0.5276 | 0.8103 | |
|
| 0.3898 | 9.0933 | 140 | 0.5047 | 0.7931 | |
|
| 0.3664 | 10.0667 | 150 | 0.5126 | 0.7586 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.45.1 |
|
- Pytorch 2.4.0 |
|
- Datasets 3.0.1 |
|
- Tokenizers 0.20.0 |
|
|
