---
license: cc-by-nc-4.0
tags:
- generated_from_trainer
metrics:
- accuracy
base_model: MCG-NJU/videomae-base-finetuned-kinetics
model-index:
- name: videomae-base-finetuned-kinetics-finetuned-rwf2000-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-rwf2000-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: 0.5482
- Accuracy: 0.7298

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4492        | 0.06  | 200  | 0.2361          | 0.905    |
| 0.3517        | 1.06  | 400  | 0.5648          | 0.8137   |
| 0.2255        | 2.06  | 600  | 0.7592          | 0.7575   |
| 0.1983        | 3.06  | 800  | 0.4803          | 0.835    |
| 0.2305        | 4.06  | 1000 | 0.4290          | 0.8738   |
| 0.1276        | 5.06  | 1200 | 0.4317          | 0.8762   |
| 0.1597        | 6.06  | 1400 | 1.3708          | 0.6937   |
| 0.3088        | 7.06  | 1600 | 0.3974          | 0.8862   |
| 0.2687        | 8.06  | 1800 | 0.5986          | 0.85     |
| 0.2085        | 9.06  | 2000 | 0.4264          | 0.8862   |
| 0.1338        | 10.06 | 2200 | 0.5015          | 0.8675   |
| 0.2191        | 11.06 | 2400 | 0.7103          | 0.845    |
| 0.2255        | 12.06 | 2600 | 0.4939          | 0.8762   |
| 0.0298        | 13.06 | 2800 | 0.6338          | 0.8612   |
| 0.0687        | 14.06 | 3000 | 0.5350          | 0.8738   |
| 0.0146        | 15.06 | 3200 | 0.4770          | 0.8838   |


### Framework versions

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