|
--- |
|
license: cc-by-nc-4.0 |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: videomae-base-finetuned-sign-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-sign-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: 3.3672 |
|
- Accuracy: 0.1905 |
|
|
|
## 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 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 8 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- training_steps: 270 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| No log | 0.04 | 11 | 2.4220 | 0.0870 | |
|
| 2.3491 | 1.04 | 22 | 2.6315 | 0.0 | |
|
| 2.3491 | 2.04 | 33 | 2.6680 | 0.0435 | |
|
| 2.2285 | 3.04 | 44 | 2.8487 | 0.1304 | |
|
| 2.2285 | 4.04 | 55 | 3.0361 | 0.0870 | |
|
| 1.996 | 5.04 | 66 | 3.0258 | 0.1304 | |
|
| 1.996 | 6.04 | 77 | 3.2125 | 0.1304 | |
|
| 1.6956 | 7.04 | 88 | 3.2063 | 0.1304 | |
|
| 1.6956 | 8.04 | 99 | 3.1919 | 0.1304 | |
|
| 1.5088 | 9.04 | 110 | 3.1940 | 0.1304 | |
|
| 1.3777 | 10.04 | 121 | 3.3180 | 0.1739 | |
|
| 1.3777 | 11.04 | 132 | 3.3112 | 0.1304 | |
|
| 1.1509 | 12.04 | 143 | 3.3400 | 0.1304 | |
|
| 1.1509 | 13.04 | 154 | 3.2550 | 0.1739 | |
|
| 0.9036 | 14.04 | 165 | 3.3682 | 0.1304 | |
|
| 0.9036 | 15.04 | 176 | 3.3775 | 0.1304 | |
|
| 0.8303 | 16.04 | 187 | 3.4701 | 0.1304 | |
|
| 0.8303 | 17.04 | 198 | 3.4340 | 0.1739 | |
|
| 0.6683 | 18.04 | 209 | 3.4843 | 0.1304 | |
|
| 0.5126 | 19.04 | 220 | 3.3552 | 0.2174 | |
|
| 0.5126 | 20.04 | 231 | 3.3702 | 0.2609 | |
|
| 0.3728 | 21.04 | 242 | 3.3871 | 0.2609 | |
|
| 0.3728 | 22.04 | 253 | 3.3565 | 0.2609 | |
|
| 0.3291 | 23.04 | 264 | 3.3861 | 0.3043 | |
|
| 0.3291 | 24.02 | 270 | 3.3876 | 0.3043 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.26.1 |
|
- Pytorch 1.13.1+cu116 |
|
- Datasets 2.9.0 |
|
- Tokenizers 0.13.2 |
|
|
