---
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
  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

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: 0.8930
- Accuracy: 0.6296

## 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: 4
- eval_batch_size: 4
- 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: 6660

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.6074        | 0.02  | 112  | 1.5690          | 0.3687   |
| 1.6001        | 1.02  | 224  | 1.5783          | 0.3041   |
| 1.4193        | 2.02  | 336  | 1.4874          | 0.3825   |
| 1.398         | 3.02  | 448  | 1.0197          | 0.6406   |
| 1.2217        | 4.02  | 560  | 1.3386          | 0.3917   |
| 1.2577        | 5.02  | 672  | 1.2196          | 0.5392   |
| 1.0121        | 6.02  | 784  | 1.2319          | 0.4793   |
| 1.2485        | 7.02  | 896  | 0.8230          | 0.7512   |
| 1.025         | 8.02  | 1008 | 0.8023          | 0.6866   |
| 1.2952        | 9.02  | 1120 | 0.9130          | 0.6037   |
| 0.9499        | 10.02 | 1232 | 1.0621          | 0.6037   |
| 0.8805        | 11.02 | 1344 | 0.8713          | 0.7051   |
| 1.2066        | 12.02 | 1456 | 0.9364          | 0.5853   |
| 0.9358        | 13.02 | 1568 | 0.9107          | 0.5853   |
| 0.9043        | 14.02 | 1680 | 0.9147          | 0.6359   |
| 0.8383        | 15.02 | 1792 | 0.9451          | 0.6359   |
| 0.7482        | 16.02 | 1904 | 0.8765          | 0.6221   |
| 0.9547        | 17.02 | 2016 | 0.7998          | 0.7650   |
| 0.7028        | 18.02 | 2128 | 0.9257          | 0.6406   |
| 0.8659        | 19.02 | 2240 | 1.0655          | 0.5853   |
| 0.5591        | 20.02 | 2352 | 1.2794          | 0.5760   |
| 0.8963        | 21.02 | 2464 | 1.0049          | 0.6959   |
| 0.9221        | 22.02 | 2576 | 1.1113          | 0.6083   |
| 0.7154        | 23.02 | 2688 | 0.9371          | 0.6406   |
| 0.8795        | 24.02 | 2800 | 0.6838          | 0.7235   |
| 0.631         | 25.02 | 2912 | 1.2093          | 0.6129   |
| 1.0489        | 26.02 | 3024 | 1.4720          | 0.5484   |
| 0.5881        | 27.02 | 3136 | 1.1905          | 0.6313   |
| 0.7919        | 28.02 | 3248 | 1.1292          | 0.5760   |
| 0.9158        | 29.02 | 3360 | 1.0214          | 0.6359   |
| 0.8319        | 30.02 | 3472 | 1.2862          | 0.6682   |
| 0.6775        | 31.02 | 3584 | 1.0971          | 0.6406   |
| 0.7191        | 32.02 | 3696 | 1.0264          | 0.6498   |
| 0.7662        | 33.02 | 3808 | 1.0589          | 0.6406   |
| 0.7313        | 34.02 | 3920 | 1.5076          | 0.5622   |
| 0.7539        | 35.02 | 4032 | 1.2265          | 0.5899   |
| 0.571         | 36.02 | 4144 | 1.1598          | 0.6267   |
| 0.3404        | 37.02 | 4256 | 1.0307          | 0.6359   |
| 0.5553        | 38.02 | 4368 | 0.8180          | 0.7235   |
| 0.8499        | 39.02 | 4480 | 1.0074          | 0.6498   |
| 0.5036        | 40.02 | 4592 | 1.1160          | 0.6313   |
| 0.814         | 41.02 | 4704 | 0.9032          | 0.6959   |
| 0.7293        | 42.02 | 4816 | 0.9331          | 0.7281   |
| 0.4402        | 43.02 | 4928 | 1.4190          | 0.5668   |
| 0.4625        | 44.02 | 5040 | 1.0268          | 0.7005   |
| 0.2266        | 45.02 | 5152 | 1.2808          | 0.6406   |
| 0.7424        | 46.02 | 5264 | 1.1821          | 0.6498   |
| 0.4852        | 47.02 | 5376 | 1.2434          | 0.6590   |
| 0.523         | 48.02 | 5488 | 1.2123          | 0.6267   |
| 0.8344        | 49.02 | 5600 | 1.1889          | 0.6636   |
| 0.6648        | 50.02 | 5712 | 1.2328          | 0.6406   |
| 0.6929        | 51.02 | 5824 | 1.3269          | 0.6129   |
| 0.4253        | 52.02 | 5936 | 1.1885          | 0.6820   |
| 0.7003        | 53.02 | 6048 | 1.1522          | 0.7005   |
| 0.4105        | 54.02 | 6160 | 1.0037          | 0.7373   |
| 0.5206        | 55.02 | 6272 | 1.0913          | 0.7189   |
| 0.7129        | 56.02 | 6384 | 1.1083          | 0.6866   |
| 0.4772        | 57.02 | 6496 | 1.1276          | 0.7143   |
| 0.4822        | 58.02 | 6608 | 1.0920          | 0.7235   |
| 0.6307        | 59.01 | 6660 | 1.0987          | 0.7189   |


### Framework versions

- Transformers 4.36.2
- Pytorch 1.13.1
- Datasets 2.16.1
- Tokenizers 0.15.0