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# 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: 0.7700
- Accuracy: 0.6713

## 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: 11100

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.638         | 0.01  | 112   | 1.5736          | 0.1567   |
| 1.5845        | 1.01  | 224   | 1.5841          | 0.2719   |
| 1.4522        | 2.01  | 336   | 1.6293          | 0.2350   |
| 1.3111        | 3.01  | 448   | 1.0450          | 0.6037   |
| 1.2849        | 4.01  | 560   | 1.3186          | 0.4608   |
| 1.3246        | 5.01  | 672   | 1.1759          | 0.5161   |
| 1.3801        | 6.01  | 784   | 1.2188          | 0.4608   |
| 1.3228        | 7.01  | 896   | 0.9895          | 0.6406   |
| 0.9706        | 8.01  | 1008  | 1.1265          | 0.6129   |
| 1.2483        | 9.01  | 1120  | 1.2352          | 0.5484   |
| 0.9394        | 10.01 | 1232  | 1.2345          | 0.4977   |
| 0.8285        | 11.01 | 1344  | 0.8702          | 0.6682   |
| 1.1175        | 12.01 | 1456  | 0.9073          | 0.6406   |
| 1.093         | 13.01 | 1568  | 0.9210          | 0.5576   |
| 0.8364        | 14.01 | 1680  | 0.9316          | 0.6590   |
| 0.766         | 15.01 | 1792  | 0.7628          | 0.7742   |
| 0.7702        | 16.01 | 1904  | 0.8982          | 0.6682   |
| 0.9184        | 17.01 | 2016  | 1.1010          | 0.6221   |
| 0.7309        | 18.01 | 2128  | 0.8245          | 0.6866   |
| 0.9575        | 19.01 | 2240  | 0.9029          | 0.7097   |
| 0.8233        | 20.01 | 2352  | 1.2445          | 0.5161   |
| 0.7643        | 21.01 | 2464  | 0.9558          | 0.6498   |
| 0.6722        | 22.01 | 2576  | 1.1864          | 0.5714   |
| 0.8441        | 23.01 | 2688  | 0.9690          | 0.7235   |
| 0.7971        | 24.01 | 2800  | 0.9349          | 0.6774   |
| 0.8296        | 25.01 | 2912  | 1.4574          | 0.4516   |
| 0.8613        | 26.01 | 3024  | 0.8688          | 0.7189   |
| 0.5614        | 27.01 | 3136  | 1.2101          | 0.6083   |
| 0.6971        | 28.01 | 3248  | 1.3006          | 0.4654   |
| 0.9642        | 29.01 | 3360  | 0.9573          | 0.6313   |
| 0.836         | 30.01 | 3472  | 1.1268          | 0.6221   |
| 0.7166        | 31.01 | 3584  | 1.2384          | 0.5622   |
| 0.9302        | 32.01 | 3696  | 1.0620          | 0.5991   |
| 0.7729        | 33.01 | 3808  | 1.3253          | 0.5622   |
| 0.8005        | 34.01 | 3920  | 1.4979          | 0.4931   |
| 0.8025        | 35.01 | 4032  | 0.9786          | 0.5668   |
| 0.881         | 36.01 | 4144  | 0.8477          | 0.6544   |
| 0.5343        | 37.01 | 4256  | 1.3107          | 0.6544   |
| 0.5611        | 38.01 | 4368  | 0.9520          | 0.6866   |
| 0.6824        | 39.01 | 4480  | 0.7909          | 0.7281   |
| 0.6146        | 40.01 | 4592  | 1.0886          | 0.6175   |
| 1.0098        | 41.01 | 4704  | 1.0434          | 0.6313   |
| 0.5555        | 42.01 | 4816  | 0.9603          | 0.6912   |
| 0.4578        | 43.01 | 4928  | 1.2341          | 0.5945   |
| 0.5883        | 44.01 | 5040  | 1.2559          | 0.6359   |
| 0.3579        | 45.01 | 5152  | 1.2459          | 0.5622   |
| 0.7936        | 46.01 | 5264  | 1.2685          | 0.6083   |
| 0.4331        | 47.01 | 5376  | 0.9118          | 0.7097   |
| 0.8989        | 48.01 | 5488  | 1.3406          | 0.5806   |
| 0.7674        | 49.01 | 5600  | 1.5231          | 0.5484   |
| 0.8136        | 50.01 | 5712  | 1.2210          | 0.6221   |
| 0.6583        | 51.01 | 5824  | 0.9262          | 0.7051   |
| 0.4305        | 52.01 | 5936  | 1.0339          | 0.6959   |
| 0.7197        | 53.01 | 6048  | 1.1948          | 0.6682   |
| 0.7143        | 54.01 | 6160  | 1.1851          | 0.6774   |
| 0.5441        | 55.01 | 6272  | 1.0351          | 0.6636   |
| 0.6443        | 56.01 | 6384  | 1.0297          | 0.6866   |
| 0.7747        | 57.01 | 6496  | 1.5174          | 0.5991   |
| 0.5943        | 58.01 | 6608  | 1.1961          | 0.6452   |
| 0.5781        | 59.01 | 6720  | 1.2187          | 0.7143   |
| 0.6913        | 60.01 | 6832  | 1.1590          | 0.6728   |
| 0.6186        | 61.01 | 6944  | 1.0495          | 0.7235   |
| 0.5185        | 62.01 | 7056  | 0.9844          | 0.7051   |
| 0.4077        | 63.01 | 7168  | 1.3194          | 0.6313   |
| 0.8217        | 64.01 | 7280  | 1.2620          | 0.6636   |
| 0.5273        | 65.01 | 7392  | 1.0395          | 0.7373   |
| 0.9002        | 66.01 | 7504  | 1.5225          | 0.5806   |
| 0.5763        | 67.01 | 7616  | 1.2559          | 0.6406   |
| 1.0535        | 68.01 | 7728  | 1.2646          | 0.6498   |
| 1.0064        | 69.01 | 7840  | 1.1533          | 0.6866   |
| 0.332         | 70.01 | 7952  | 1.0438          | 0.7005   |
| 0.3978        | 71.01 | 8064  | 1.0248          | 0.7051   |
| 0.4459        | 72.01 | 8176  | 1.0926          | 0.7465   |
| 0.511         | 73.01 | 8288  | 1.1233          | 0.7143   |
| 0.7933        | 74.01 | 8400  | 1.1535          | 0.7189   |
| 0.3739        | 75.01 | 8512  | 1.3056          | 0.6912   |
| 0.6976        | 76.01 | 8624  | 1.3159          | 0.6682   |
| 0.5453        | 77.01 | 8736  | 1.4541          | 0.6359   |
| 0.2915        | 78.01 | 8848  | 1.2601          | 0.7051   |
| 0.6552        | 79.01 | 8960  | 1.5338          | 0.6544   |
| 0.5067        | 80.01 | 9072  | 1.6630          | 0.6037   |
| 0.5134        | 81.01 | 9184  | 1.4740          | 0.6406   |
| 0.7271        | 82.01 | 9296  | 1.2171          | 0.7097   |
| 0.719         | 83.01 | 9408  | 1.3653          | 0.6406   |
| 0.1955        | 84.01 | 9520  | 1.4696          | 0.6544   |
| 0.5761        | 85.01 | 9632  | 1.3334          | 0.6636   |
| 0.7094        | 86.01 | 9744  | 1.2673          | 0.6912   |
| 0.5186        | 87.01 | 9856  | 1.3147          | 0.6866   |
| 0.6876        | 88.01 | 9968  | 1.2622          | 0.7051   |
| 0.4912        | 89.01 | 10080 | 1.3054          | 0.7189   |
| 0.194         | 90.01 | 10192 | 1.3244          | 0.6959   |
| 0.6916        | 91.01 | 10304 | 1.1800          | 0.7327   |
| 0.5735        | 92.01 | 10416 | 1.1056          | 0.7419   |
| 0.2122        | 93.01 | 10528 | 1.1070          | 0.7281   |
| 0.1434        | 94.01 | 10640 | 1.1776          | 0.7097   |
| 0.4681        | 95.01 | 10752 | 1.1505          | 0.7327   |
| 0.2856        | 96.01 | 10864 | 1.1203          | 0.7235   |
| 0.6509        | 97.01 | 10976 | 1.1502          | 0.7189   |
| 0.1881        | 98.01 | 11088 | 1.1474          | 0.7189   |
| 0.5577        | 99.0  | 11100 | 1.1473          | 0.7189   |


### Framework versions

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

{"license": "cc-by-nc-4.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "MCG-NJU/videomae-base", "model-index": [{"name": "videomae-base-finetuned-subset", "results": []}]}
transformers tensorboard safetensors videomae video-classification generated_from_trainer base_model:MCG-NJU/videomae-base license:cc-by-nc-4.0 endpoints_compatible region:us