---
license: cc-by-nc-4.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-large-finetuned-kinetics-finetuned-rwf2000-epochs8-batch8-kl-torch2
  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-large-finetuned-kinetics-finetuned-rwf2000-epochs8-batch8-kl-torch2

This model is a fine-tuned version of [MCG-NJU/videomae-large-finetuned-kinetics](https://huggingface.co/MCG-NJU/videomae-large-finetuned-kinetics) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6146
- Accuracy: 0.7212

## 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.361         | 0.06  | 200  | 0.2425          | 0.895    |
| 0.3449        | 1.06  | 400  | 0.6639          | 0.68     |
| 0.2435        | 2.06  | 600  | 0.9180          | 0.6663   |
| 0.2001        | 3.06  | 800  | 0.5656          | 0.7662   |
| 0.1405        | 4.06  | 1000 | 0.3859          | 0.86     |
| 0.1845        | 5.06  | 1200 | 0.3825          | 0.8675   |
| 0.1586        | 6.06  | 1400 | 1.4446          | 0.6687   |
| 0.2013        | 7.06  | 1600 | 0.4730          | 0.8562   |
| 0.2113        | 8.06  | 1800 | 0.3328          | 0.8862   |
| 0.245         | 9.06  | 2000 | 0.3519          | 0.8938   |
| 0.1767        | 10.06 | 2200 | 0.4004          | 0.895    |
| 0.1688        | 11.06 | 2400 | 0.6468          | 0.86     |
| 0.2823        | 12.06 | 2600 | 0.6006          | 0.8575   |
| 0.0928        | 13.06 | 2800 | 0.5516          | 0.875    |
| 0.0079        | 14.06 | 3000 | 0.5855          | 0.87     |
| 0.0325        | 15.06 | 3200 | 0.4921          | 0.8925   |


### Framework versions

- Transformers 4.27.4
- Pytorch 2.0.0+cu117
- Datasets 2.11.0
- Tokenizers 0.13.2