---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-finetuned-subset-check10
  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-subset-check10

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: 0.6927
- Accuracy: 0.6667

## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- 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: 1110

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.6348        | 0.05  | 56   | 1.5443          | 0.5115   |
| 1.6015        | 1.05  | 112  | 1.5298          | 0.4793   |
| 1.5683        | 2.05  | 168  | 1.5289          | 0.3272   |
| 1.512         | 3.05  | 224  | 1.3029          | 0.6313   |
| 1.2309        | 4.05  | 280  | 1.2181          | 0.5207   |
| 1.1949        | 5.05  | 336  | 1.0441          | 0.6590   |
| 1.0987        | 6.05  | 392  | 1.0041          | 0.6129   |
| 1.148         | 7.05  | 448  | 1.0259          | 0.6175   |
| 0.9958        | 8.05  | 504  | 0.9508          | 0.6728   |
| 1.0856        | 9.05  | 560  | 1.0041          | 0.5945   |
| 0.8809        | 10.05 | 616  | 0.9638          | 0.6359   |
| 0.9185        | 11.05 | 672  | 0.9248          | 0.6820   |
| 0.9136        | 12.05 | 728  | 1.0136          | 0.6728   |
| 0.8537        | 13.05 | 784  | 0.8515          | 0.7189   |
| 0.7921        | 14.05 | 840  | 0.8222          | 0.7005   |
| 0.7313        | 15.05 | 896  | 0.7512          | 0.7419   |
| 0.5998        | 16.05 | 952  | 0.9410          | 0.6129   |
| 0.8093        | 17.05 | 1008 | 0.8145          | 0.7051   |
| 0.604         | 18.05 | 1064 | 0.9014          | 0.6820   |
| 0.7066        | 19.04 | 1110 | 0.8935          | 0.6682   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.1
- Datasets 2.16.1
- Tokenizers 0.15.0