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# videomae-base-finetuned-ucf101-subset-finetuned-subset-0401

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: 0.7418
- Accuracy: 0.7269

## 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: 2775

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.6151        | 0.02  | 56   | 1.5567          | 0.2949   |
| 1.3399        | 1.02  | 112  | 1.2929          | 0.3825   |
| 1.2751        | 2.02  | 168  | 1.4618          | 0.3134   |
| 1.3725        | 3.02  | 224  | 0.9080          | 0.6498   |
| 1.0782        | 4.02  | 280  | 1.1473          | 0.5300   |
| 1.1514        | 5.02  | 336  | 0.8953          | 0.6359   |
| 1.0593        | 6.02  | 392  | 1.3372          | 0.4608   |
| 1.1193        | 7.02  | 448  | 0.9655          | 0.6313   |
| 0.719         | 8.02  | 504  | 0.8527          | 0.6728   |
| 1.0157        | 9.02  | 560  | 1.2763          | 0.5023   |
| 0.6991        | 10.02 | 616  | 0.8840          | 0.6406   |
| 0.9019        | 11.02 | 672  | 0.8941          | 0.6636   |
| 0.7456        | 12.02 | 728  | 1.0455          | 0.6037   |
| 0.6631        | 13.02 | 784  | 0.6456          | 0.7558   |
| 0.7143        | 14.02 | 840  | 0.8887          | 0.6682   |
| 0.6639        | 15.02 | 896  | 0.6863          | 0.7604   |
| 0.5195        | 16.02 | 952  | 0.9475          | 0.6221   |
| 0.9211        | 17.02 | 1008 | 0.7339          | 0.7373   |
| 0.5328        | 18.02 | 1064 | 0.9085          | 0.6544   |
| 0.6818        | 19.02 | 1120 | 0.7977          | 0.7097   |
| 0.6132        | 20.02 | 1176 | 0.7116          | 0.7373   |
| 0.4113        | 21.02 | 1232 | 1.0191          | 0.5853   |
| 0.7443        | 22.02 | 1288 | 1.2705          | 0.5714   |
| 0.6904        | 23.02 | 1344 | 0.8419          | 0.6636   |
| 0.5888        | 24.02 | 1400 | 0.7481          | 0.6959   |
| 0.6739        | 25.02 | 1456 | 0.9970          | 0.7097   |
| 0.6595        | 26.02 | 1512 | 1.3474          | 0.5806   |
| 0.5574        | 27.02 | 1568 | 0.6245          | 0.7926   |
| 0.5627        | 28.02 | 1624 | 0.7718          | 0.7143   |
| 0.6417        | 29.02 | 1680 | 0.6506          | 0.7604   |
| 0.3854        | 30.02 | 1736 | 0.9524          | 0.6544   |
| 0.354         | 31.02 | 1792 | 1.0662          | 0.5945   |
| 0.7568        | 32.02 | 1848 | 0.7329          | 0.7604   |
| 0.5359        | 33.02 | 1904 | 0.8958          | 0.6774   |
| 0.5946        | 34.02 | 1960 | 0.8312          | 0.6912   |
| 0.5673        | 35.02 | 2016 | 0.7245          | 0.7051   |
| 0.4291        | 36.02 | 2072 | 0.8294          | 0.6912   |
| 0.5245        | 37.02 | 2128 | 0.8931          | 0.7005   |
| 0.4113        | 38.02 | 2184 | 0.7470          | 0.6912   |
| 0.456         | 39.02 | 2240 | 0.8325          | 0.6728   |
| 0.6955        | 40.02 | 2296 | 0.6941          | 0.7788   |
| 0.6283        | 41.02 | 2352 | 0.9662          | 0.6636   |
| 0.6465        | 42.02 | 2408 | 1.1286          | 0.6129   |
| 0.4387        | 43.02 | 2464 | 0.9525          | 0.6175   |
| 0.2879        | 44.02 | 2520 | 1.0277          | 0.6313   |
| 0.5188        | 45.02 | 2576 | 1.0631          | 0.6359   |
| 0.4464        | 46.02 | 2632 | 0.9313          | 0.6359   |
| 0.6155        | 47.02 | 2688 | 0.9699          | 0.6267   |
| 0.3921        | 48.02 | 2744 | 1.0027          | 0.6313   |
| 0.3345        | 49.01 | 2775 | 1.0278          | 0.6221   |


### 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-0401", "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