---
license: cc-by-nc-4.0
base_model: abduldattijo/videomae-base-finetuned-ucf101-subset
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-finetuned-ucf101-subset-V3KILLER
  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-finetuned-ucf101-subset-V3KILLER

This model is a fine-tuned version of [abduldattijo/videomae-base-finetuned-ucf101-subset](https://huggingface.co./abduldattijo/videomae-base-finetuned-ucf101-subset) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2181
- Accuracy: 0.9615

## 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: 5960

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3447        | 0.03  | 150  | 0.1339          | 0.9579   |
| 0.3161        | 1.03  | 300  | 0.1538          | 0.9465   |
| 0.3386        | 2.03  | 450  | 0.3260          | 0.9019   |
| 0.3572        | 3.03  | 600  | 0.1967          | 0.9311   |
| 0.3699        | 4.03  | 750  | 0.1661          | 0.9505   |
| 0.3125        | 5.03  | 900  | 0.3292          | 0.9205   |
| 0.4785        | 6.03  | 1050 | 0.2029          | 0.9324   |
| 0.3477        | 7.03  | 1200 | 0.1534          | 0.9385   |
| 0.2909        | 8.03  | 1350 | 0.1265          | 0.9571   |
| 0.2646        | 9.03  | 1500 | 0.1239          | 0.9586   |
| 0.3339        | 10.03 | 1650 | 0.1341          | 0.9628   |
| 0.0954        | 11.03 | 1800 | 0.1835          | 0.9423   |
| 0.3861        | 12.03 | 1950 | 0.2241          | 0.9467   |
| 0.248         | 13.03 | 2100 | 0.1258          | 0.9620   |
| 0.2513        | 14.03 | 2250 | 0.2217          | 0.9357   |
| 0.1133        | 15.03 | 2400 | 0.2129          | 0.9406   |
| 0.1421        | 16.03 | 2550 | 0.3006          | 0.9264   |
| 0.0248        | 17.03 | 2700 | 0.3868          | 0.9142   |
| 0.0166        | 18.03 | 2850 | 0.2594          | 0.9518   |
| 0.0874        | 19.03 | 3000 | 0.3652          | 0.9252   |
| 0.0889        | 20.03 | 3150 | 0.2249          | 0.9533   |
| 0.0804        | 21.03 | 3300 | 0.2027          | 0.9628   |
| 0.0019        | 22.03 | 3450 | 0.4682          | 0.9212   |
| 0.0405        | 23.03 | 3600 | 0.2425          | 0.9493   |
| 0.0847        | 24.03 | 3750 | 0.2456          | 0.9558   |
| 0.1656        | 25.03 | 3900 | 0.2623          | 0.9505   |
| 0.1007        | 26.03 | 4050 | 0.2389          | 0.9484   |
| 0.0616        | 27.03 | 4200 | 0.2529          | 0.9543   |
| 0.0005        | 28.03 | 4350 | 0.1521          | 0.9732   |
| 0.0006        | 29.03 | 4500 | 0.4115          | 0.9165   |
| 0.0007        | 30.03 | 4650 | 0.4279          | 0.9220   |
| 0.0004        | 31.03 | 4800 | 0.3572          | 0.9372   |
| 0.0003        | 32.03 | 4950 | 0.3314          | 0.9419   |
| 0.0002        | 33.03 | 5100 | 0.4008          | 0.9347   |
| 0.0611        | 34.03 | 5250 | 0.4632          | 0.9239   |
| 0.0003        | 35.03 | 5400 | 0.3756          | 0.9368   |
| 0.0003        | 36.03 | 5550 | 0.3745          | 0.9429   |
| 0.163         | 37.03 | 5700 | 0.3967          | 0.9383   |
| 0.0059        | 38.03 | 5850 | 0.3808          | 0.9389   |
| 0.0003        | 39.02 | 5960 | 0.3824          | 0.9395   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.1+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0