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# videomae-base-finetuned-ucf101-subset-finetuned-subset

This model is a fine-tuned version of [NiiCole/videomae-base-finetuned-ucf101-subset](https://huggingface.co/NiiCole/videomae-base-finetuned-ucf101-subset) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5670
- Accuracy: 0.8165

## 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: 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: 3510

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.58          | 0.02  | 59   | 1.5476          | 0.3733   |
| 1.3617        | 1.02  | 118  | 1.2123          | 0.4977   |
| 1.1668        | 2.02  | 177  | 1.3331          | 0.3825   |
| 1.1751        | 3.02  | 236  | 1.2529          | 0.3687   |
| 0.9961        | 4.02  | 295  | 1.0008          | 0.6452   |
| 1.0562        | 5.02  | 354  | 1.0535          | 0.5392   |
| 1.0189        | 6.02  | 413  | 0.9321          | 0.6866   |
| 0.8553        | 7.02  | 472  | 0.8955          | 0.5853   |
| 0.8961        | 8.02  | 531  | 0.7889          | 0.7419   |
| 1.1626        | 9.02  | 590  | 0.9532          | 0.6175   |
| 0.7951        | 10.02 | 649  | 1.1165          | 0.5530   |
| 0.9042        | 11.02 | 708  | 0.7012          | 0.7650   |
| 0.8642        | 12.02 | 767  | 0.7589          | 0.6774   |
| 0.8017        | 13.02 | 826  | 0.7485          | 0.6959   |
| 0.7523        | 14.02 | 885  | 0.5617          | 0.7834   |
| 0.7223        | 15.02 | 944  | 1.0344          | 0.6129   |
| 0.6164        | 16.02 | 1003 | 0.7275          | 0.7419   |
| 0.6892        | 17.02 | 1062 | 0.6162          | 0.7788   |
| 0.7865        | 18.02 | 1121 | 0.7966          | 0.6590   |
| 0.6387        | 19.02 | 1180 | 0.7436          | 0.6774   |
| 0.6181        | 20.02 | 1239 | 0.7137          | 0.7373   |
| 0.6085        | 21.02 | 1298 | 0.9581          | 0.6682   |
| 0.7109        | 22.02 | 1357 | 0.7746          | 0.7097   |
| 0.7686        | 23.02 | 1416 | 0.7969          | 0.7097   |
| 0.5995        | 24.02 | 1475 | 1.0075          | 0.6129   |
| 0.5854        | 25.02 | 1534 | 0.7389          | 0.7419   |
| 0.575         | 26.02 | 1593 | 0.7198          | 0.7143   |
| 0.7478        | 27.02 | 1652 | 0.6098          | 0.7742   |
| 0.7204        | 28.02 | 1711 | 0.6459          | 0.7972   |
| 0.4325        | 29.02 | 1770 | 0.7268          | 0.7512   |
| 0.593         | 30.02 | 1829 | 0.5901          | 0.7880   |
| 0.6432        | 31.02 | 1888 | 0.5924          | 0.7880   |
| 0.4821        | 32.02 | 1947 | 0.5730          | 0.8157   |
| 0.9189        | 33.02 | 2006 | 0.6242          | 0.7834   |
| 0.6179        | 34.02 | 2065 | 0.5847          | 0.8018   |
| 0.5767        | 35.02 | 2124 | 0.5965          | 0.8249   |
| 0.5298        | 36.02 | 2183 | 0.7918          | 0.7235   |
| 0.5651        | 37.02 | 2242 | 0.8338          | 0.7327   |
| 0.9236        | 38.02 | 2301 | 0.8371          | 0.7143   |
| 0.4854        | 39.02 | 2360 | 0.7115          | 0.7696   |
| 0.4837        | 40.02 | 2419 | 0.6326          | 0.7696   |
| 0.4142        | 41.02 | 2478 | 0.6266          | 0.8203   |
| 0.3309        | 42.02 | 2537 | 0.5806          | 0.8111   |
| 0.3939        | 43.02 | 2596 | 0.5746          | 0.8249   |
| 0.4993        | 44.02 | 2655 | 0.6114          | 0.8387   |
| 0.3785        | 45.02 | 2714 | 0.6317          | 0.8018   |
| 0.5224        | 46.02 | 2773 | 0.6667          | 0.7972   |
| 0.5705        | 47.02 | 2832 | 0.6382          | 0.7926   |
| 0.3342        | 48.02 | 2891 | 0.5592          | 0.8157   |
| 0.5044        | 49.02 | 2950 | 0.5748          | 0.7926   |
| 0.3838        | 50.02 | 3009 | 0.6050          | 0.7788   |
| 0.5099        | 51.02 | 3068 | 0.6557          | 0.7604   |
| 0.4335        | 52.02 | 3127 | 0.7119          | 0.7512   |
| 0.4122        | 53.02 | 3186 | 0.6562          | 0.7788   |
| 0.4431        | 54.02 | 3245 | 0.6701          | 0.7650   |
| 0.4536        | 55.02 | 3304 | 0.6659          | 0.7696   |
| 0.3867        | 56.02 | 3363 | 0.6632          | 0.7788   |
| 0.3878        | 57.02 | 3422 | 0.6911          | 0.7742   |
| 0.3853        | 58.02 | 3481 | 0.6931          | 0.7788   |
| 0.3268        | 59.01 | 3510 | 0.6914          | 0.7788   |


### Framework versions

- Transformers 4.35.2
- Pytorch 1.13.1
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "cc-by-nc-4.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "NiiCole/videomae-base-finetuned-ucf101-subset", "model-index": [{"name": "videomae-base-finetuned-ucf101-subset-finetuned-subset", "results": []}]}
transformers tensorboard safetensors videomae video-classification generated_from_trainer base_model:NiiCole/videomae-base-finetuned-ucf101-subset license:cc-by-nc-4.0 endpoints_compatible region:us