transformers pytorch videomae video-classification generated_from_trainer base_model:MCG-NJU/videomae-base license:cc-by-nc-4.0 endpoints_compatible region:us
---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-finetuned-camera_move-subset
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# videomae-base-finetuned-camera_move-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: 2.0146
- Accuracy: 0.7285

## 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: 4e-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: 13000

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.4019        | 0.01  | 131   | 1.0423          | 0.5960   |
| 1.0428        | 1.01  | 262   | 0.9115          | 0.6291   |
| 0.8694        | 2.01  | 393   | 0.8362          | 0.6424   |
| 0.6894        | 3.01  | 524   | 0.7107          | 0.7086   |
| 0.6741        | 4.01  | 655   | 0.6441          | 0.7219   |
| 0.5955        | 5.01  | 786   | 0.8368          | 0.6821   |
| 0.5898        | 6.01  | 917   | 0.7774          | 0.7152   |
| 0.5252        | 7.01  | 1048  | 0.6022          | 0.7682   |
| 0.453         | 8.01  | 1179  | 0.6388          | 0.7881   |
| 0.4625        | 9.01  | 1310  | 0.8417          | 0.7152   |
| 0.465         | 10.01 | 1441  | 0.8575          | 0.6954   |
| 0.5106        | 11.01 | 1572  | 0.7849          | 0.7616   |
| 0.4138        | 12.01 | 1703  | 0.9293          | 0.7086   |
| 0.3526        | 13.01 | 1834  | 1.2684          | 0.6225   |
| 0.3645        | 14.01 | 1965  | 0.9428          | 0.7285   |
| 0.2778        | 15.01 | 2096  | 1.0217          | 0.6821   |
| 0.2821        | 16.01 | 2227  | 1.3365          | 0.6623   |
| 0.2654        | 17.01 | 2358  | 1.0170          | 0.7550   |
| 0.2961        | 18.01 | 2489  | 1.3952          | 0.7152   |
| 0.1987        | 19.01 | 2620  | 1.4083          | 0.6954   |
| 0.1832        | 20.01 | 2751  | 1.5808          | 0.6689   |
| 0.2035        | 21.01 | 2882  | 1.2864          | 0.7483   |
| 0.1608        | 22.01 | 3013  | 1.7499          | 0.6755   |
| 0.2171        | 23.01 | 3144  | 1.2574          | 0.7417   |
| 0.1824        | 24.01 | 3275  | 1.4203          | 0.7483   |
| 0.152         | 25.01 | 3406  | 1.4163          | 0.7351   |
| 0.1512        | 26.01 | 3537  | 1.5550          | 0.7086   |
| 0.1635        | 27.01 | 3668  | 1.2334          | 0.7682   |
| 0.1371        | 28.01 | 3799  | 1.5798          | 0.7417   |
| 0.1048        | 29.01 | 3930  | 1.6993          | 0.7219   |
| 0.097         | 30.01 | 4061  | 1.8505          | 0.6887   |
| 0.1662        | 31.01 | 4192  | 1.5091          | 0.7417   |
| 0.0957        | 32.01 | 4323  | 1.5388          | 0.7285   |
| 0.0967        | 33.01 | 4454  | 1.6766          | 0.7219   |
| 0.1581        | 34.01 | 4585  | 1.5444          | 0.7550   |
| 0.0967        | 35.01 | 4716  | 1.6108          | 0.7219   |
| 0.1013        | 36.01 | 4847  | 1.6734          | 0.7417   |
| 0.0691        | 37.01 | 4978  | 1.5116          | 0.7616   |
| 0.1161        | 38.01 | 5109  | 1.6343          | 0.7285   |
| 0.0847        | 39.01 | 5240  | 1.6119          | 0.7616   |
| 0.0769        | 40.01 | 5371  | 1.8494          | 0.7285   |
| 0.0604        | 41.01 | 5502  | 1.9854          | 0.7020   |
| 0.0845        | 42.01 | 5633  | 1.9722          | 0.7020   |
| 0.0808        | 43.01 | 5764  | 1.9046          | 0.7219   |
| 0.091         | 44.01 | 5895  | 1.8344          | 0.7152   |
| 0.1249        | 45.01 | 6026  | 1.7306          | 0.7219   |
| 0.0602        | 46.01 | 6157  | 1.8982          | 0.7550   |
| 0.0901        | 47.01 | 6288  | 1.9487          | 0.6954   |
| 0.081         | 48.01 | 6419  | 1.6702          | 0.7417   |
| 0.0336        | 49.01 | 6550  | 1.5591          | 0.7682   |
| 0.0975        | 50.01 | 6681  | 1.9009          | 0.7086   |
| 0.0697        | 51.01 | 6812  | 1.6135          | 0.7616   |
| 0.0474        | 52.01 | 6943  | 1.5886          | 0.7682   |
| 0.0427        | 53.01 | 7074  | 1.6915          | 0.7616   |
| 0.0774        | 54.01 | 7205  | 1.7434          | 0.7417   |
| 0.0685        | 55.01 | 7336  | 1.9552          | 0.7152   |
| 0.0531        | 56.01 | 7467  | 1.7448          | 0.7550   |
| 0.0371        | 57.01 | 7598  | 1.8175          | 0.7483   |
| 0.0244        | 58.01 | 7729  | 1.9252          | 0.7351   |
| 0.0317        | 59.01 | 7860  | 2.1868          | 0.6954   |
| 0.0813        | 60.01 | 7991  | 1.8846          | 0.7417   |
| 0.0857        | 61.01 | 8122  | 1.7532          | 0.7285   |
| 0.0424        | 62.01 | 8253  | 1.8003          | 0.7550   |
| 0.0481        | 63.01 | 8384  | 1.7935          | 0.7351   |
| 0.0495        | 64.01 | 8515  | 2.0369          | 0.7219   |
| 0.0217        | 65.01 | 8646  | 2.0552          | 0.7219   |
| 0.0303        | 66.01 | 8777  | 1.8629          | 0.7417   |
| 0.0439        | 67.01 | 8908  | 1.9953          | 0.7417   |
| 0.0518        | 68.01 | 9039  | 1.9958          | 0.7351   |
| 0.0295        | 69.01 | 9170  | 1.8984          | 0.7616   |
| 0.0485        | 70.01 | 9301  | 1.7583          | 0.7483   |
| 0.0149        | 71.01 | 9432  | 1.8815          | 0.7351   |
| 0.0107        | 72.01 | 9563  | 1.8341          | 0.7616   |
| 0.0475        | 73.01 | 9694  | 1.7961          | 0.7351   |
| 0.0318        | 74.01 | 9825  | 2.0999          | 0.7285   |
| 0.0108        | 75.01 | 9956  | 2.0441          | 0.7219   |
| 0.0085        | 76.01 | 10087 | 1.9867          | 0.7351   |
| 0.0278        | 77.01 | 10218 | 1.7968          | 0.7682   |
| 0.0106        | 78.01 | 10349 | 1.8662          | 0.7682   |
| 0.0241        | 79.01 | 10480 | 1.8388          | 0.7682   |
| 0.0303        | 80.01 | 10611 | 1.8758          | 0.7682   |
| 0.0199        | 81.01 | 10742 | 1.9275          | 0.7483   |
| 0.0052        | 82.01 | 10873 | 1.8741          | 0.7417   |
| 0.007         | 83.01 | 11004 | 2.0243          | 0.7219   |
| 0.0101        | 84.01 | 11135 | 1.9947          | 0.7285   |
| 0.0184        | 85.01 | 11266 | 1.9342          | 0.7417   |
| 0.0062        | 86.01 | 11397 | 2.0611          | 0.7351   |
| 0.018         | 87.01 | 11528 | 1.9867          | 0.7550   |
| 0.0194        | 88.01 | 11659 | 1.8631          | 0.7483   |
| 0.0396        | 89.01 | 11790 | 1.9126          | 0.7417   |
| 0.0048        | 90.01 | 11921 | 1.8788          | 0.7351   |
| 0.0044        | 91.01 | 12052 | 1.8962          | 0.7351   |
| 0.0033        | 92.01 | 12183 | 1.9455          | 0.7351   |
| 0.0052        | 93.01 | 12314 | 1.9772          | 0.7351   |
| 0.0068        | 94.01 | 12445 | 2.0047          | 0.7351   |
| 0.0046        | 95.01 | 12576 | 2.0135          | 0.7351   |
| 0.0158        | 96.01 | 12707 | 2.0176          | 0.7351   |
| 0.0074        | 97.01 | 12838 | 2.0148          | 0.7285   |
| 0.0016        | 98.01 | 12969 | 2.0152          | 0.7285   |
| 0.0051        | 99.0  | 13000 | 2.0146          | 0.7285   |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3
