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---
license: cc-by-nc-4.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-finetuned-engine-subset-20230310
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-engine-subset-20230310
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: 0.4958
- Accuracy: 0.85
## 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: 6
- eval_batch_size: 6
- 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: 600
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.5947 | 0.05 | 31 | 2.5383 | 0.15 |
| 2.4195 | 1.05 | 62 | 2.5108 | 0.15 |
| 2.2476 | 2.05 | 93 | 2.0533 | 0.225 |
| 1.9449 | 3.05 | 124 | 2.0719 | 0.2375 |
| 1.5724 | 4.05 | 155 | 1.4756 | 0.475 |
| 1.395 | 5.05 | 186 | 1.2884 | 0.5 |
| 1.0822 | 6.05 | 217 | 1.0679 | 0.575 |
| 1.0635 | 7.05 | 248 | 0.8040 | 0.7 |
| 0.8707 | 8.05 | 279 | 0.9334 | 0.525 |
| 0.7042 | 9.05 | 310 | 0.6477 | 0.75 |
| 0.6543 | 10.05 | 341 | 0.6963 | 0.7375 |
| 0.6807 | 11.05 | 372 | 0.4958 | 0.85 |
| 0.4924 | 12.05 | 403 | 0.6374 | 0.775 |
| 0.4822 | 13.05 | 434 | 0.6145 | 0.75 |
| 0.4878 | 14.05 | 465 | 0.6274 | 0.7625 |
| 0.4442 | 15.05 | 496 | 0.4231 | 0.85 |
| 0.2739 | 16.05 | 527 | 0.4999 | 0.85 |
| 0.3514 | 17.05 | 558 | 0.4639 | 0.8375 |
| 0.4158 | 18.05 | 589 | 0.4291 | 0.85 |
| 0.2689 | 19.02 | 600 | 0.4294 | 0.85 |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.12.1+cu113
- Datasets 2.10.1
- Tokenizers 0.13.2
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