---
license: cc-by-nc-4.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-ipm_all_videos
  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-ipm_all_videos

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: 0.4713
- Accuracy: 0.8559

## 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: 3600

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.7831        | 0.02  | 60   | 1.8965          | 0.1186   |
| 1.7706        | 1.02  | 120  | 1.9115          | 0.1186   |
| 1.7497        | 2.02  | 180  | 1.8985          | 0.1356   |
| 1.5214        | 3.02  | 240  | 1.4807          | 0.3475   |
| 1.1458        | 4.02  | 300  | 1.7024          | 0.3559   |
| 1.1587        | 5.02  | 360  | 1.6771          | 0.2966   |
| 0.9256        | 6.02  | 420  | 1.6428          | 0.3814   |
| 1.265         | 7.02  | 480  | 1.5169          | 0.5      |
| 0.8271        | 8.02  | 540  | 1.0310          | 0.5847   |
| 0.6011        | 9.02  | 600  | 1.1739          | 0.5508   |
| 0.9542        | 10.02 | 660  | 1.3323          | 0.5424   |
| 1.1231        | 11.02 | 720  | 1.4279          | 0.4915   |
| 0.728         | 12.02 | 780  | 2.1913          | 0.4661   |
| 0.5991        | 13.02 | 840  | 1.1088          | 0.6271   |
| 1.0613        | 14.02 | 900  | 1.3781          | 0.5      |
| 0.9121        | 15.02 | 960  | 1.4224          | 0.5424   |
| 0.6083        | 16.02 | 1020 | 0.8779          | 0.6695   |
| 0.408         | 17.02 | 1080 | 0.8512          | 0.7119   |
| 0.3741        | 18.02 | 1140 | 0.8884          | 0.7034   |
| 0.8906        | 19.02 | 1200 | 1.1396          | 0.6017   |
| 0.568         | 20.02 | 1260 | 0.7380          | 0.6949   |
| 0.4135        | 21.02 | 1320 | 0.7966          | 0.6525   |
| 0.5492        | 22.02 | 1380 | 0.9815          | 0.6780   |
| 0.902         | 23.02 | 1440 | 0.9267          | 0.6441   |
| 0.6889        | 24.02 | 1500 | 1.4313          | 0.5763   |
| 0.788         | 25.02 | 1560 | 1.2156          | 0.5678   |
| 0.7324        | 26.02 | 1620 | 0.8015          | 0.6780   |
| 0.6733        | 27.02 | 1680 | 0.8682          | 0.6949   |
| 0.498         | 28.02 | 1740 | 0.8767          | 0.6949   |
| 0.5558        | 29.02 | 1800 | 0.9248          | 0.6780   |
| 0.5583        | 30.02 | 1860 | 1.1784          | 0.6356   |
| 0.3905        | 31.02 | 1920 | 1.0646          | 0.6864   |
| 0.3728        | 32.02 | 1980 | 0.8338          | 0.7797   |
| 0.5988        | 33.02 | 2040 | 0.8339          | 0.7542   |
| 0.3636        | 34.02 | 2100 | 0.7577          | 0.7627   |
| 0.505         | 35.02 | 2160 | 1.0310          | 0.6864   |
| 0.5344        | 36.02 | 2220 | 0.6345          | 0.7458   |
| 0.2814        | 37.02 | 2280 | 0.9954          | 0.7119   |
| 0.2187        | 38.02 | 2340 | 0.7515          | 0.7797   |
| 0.4876        | 39.02 | 2400 | 0.8392          | 0.7627   |
| 0.1148        | 40.02 | 2460 | 0.6182          | 0.8729   |
| 0.3139        | 41.02 | 2520 | 1.1651          | 0.6949   |
| 0.2638        | 42.02 | 2580 | 0.8299          | 0.7797   |
| 0.1989        | 43.02 | 2640 | 0.5943          | 0.8220   |
| 0.5473        | 44.02 | 2700 | 0.6514          | 0.8644   |
| 0.3921        | 45.02 | 2760 | 0.6708          | 0.8220   |
| 0.1756        | 46.02 | 2820 | 0.5431          | 0.8305   |
| 0.1089        | 47.02 | 2880 | 0.6040          | 0.8136   |
| 0.3616        | 48.02 | 2940 | 0.5281          | 0.8475   |
| 0.2752        | 49.02 | 3000 | 0.6430          | 0.8305   |
| 0.3847        | 50.02 | 3060 | 0.5640          | 0.8644   |
| 0.0909        | 51.02 | 3120 | 0.5178          | 0.8559   |
| 0.3426        | 52.02 | 3180 | 0.3770          | 0.8983   |
| 0.0516        | 53.02 | 3240 | 0.5365          | 0.8390   |
| 0.2133        | 54.02 | 3300 | 0.5919          | 0.8475   |
| 0.1382        | 55.02 | 3360 | 0.5112          | 0.8390   |
| 0.1803        | 56.02 | 3420 | 0.5173          | 0.8475   |
| 0.1352        | 57.02 | 3480 | 0.5207          | 0.8390   |
| 0.4445        | 58.02 | 3540 | 0.4763          | 0.8559   |
| 0.3249        | 59.02 | 3600 | 0.4713          | 0.8559   |


### Framework versions

- Transformers 4.29.1
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3