---
license: cc-by-nc-4.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-finetuned-kinetics-finetuned-rwf2000mp4-epochs8-batch8-kb
  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-kinetics-finetuned-rwf2000mp4-epochs8-batch8-kb

This model is a fine-tuned version of [MCG-NJU/videomae-base-finetuned-kinetics](https://huggingface.co/MCG-NJU/videomae-base-finetuned-kinetics) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8559
- Accuracy: 0.7453

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 3200

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3514        | 0.06  | 200  | 0.2837          | 0.8875   |
| 0.3156        | 1.06  | 400  | 0.6930          | 0.7625   |
| 0.2273        | 2.06  | 600  | 0.5692          | 0.805    |
| 0.2091        | 3.06  | 800  | 0.3872          | 0.8612   |
| 0.1875        | 4.06  | 1000 | 0.3394          | 0.8725   |
| 0.1206        | 5.06  | 1200 | 0.4416          | 0.8562   |
| 0.1302        | 6.06  | 1400 | 1.0851          | 0.7475   |
| 0.3417        | 7.06  | 1600 | 0.5024          | 0.8638   |
| 0.2545        | 8.06  | 1800 | 0.3819          | 0.9      |
| 0.1787        | 9.06  | 2000 | 0.3864          | 0.8962   |
| 0.0761        | 10.06 | 2200 | 0.5604          | 0.8562   |
| 0.076         | 11.06 | 2400 | 0.5780          | 0.8725   |
| 0.1476        | 12.06 | 2600 | 0.5479          | 0.8725   |
| 0.1274        | 13.06 | 2800 | 0.5843          | 0.87     |
| 0.0382        | 14.06 | 3000 | 0.6739          | 0.8525   |
| 0.0143        | 15.06 | 3200 | 0.5568          | 0.8738   |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.1+cu117
- Datasets 2.8.0
- Tokenizers 0.13.2