---
library_name: transformers
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base-finetuned-kinetics
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: VideoMAE_4_CLASS_QUALITY_CHECK
  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_4_CLASS_QUALITY_CHECK

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: 0.0015
- Accuracy: 1.0

## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 350
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 6.0723        | 0.02   | 7    | 1.3154          | 0.4286   |
| 4.5479        | 1.0214 | 15   | 1.0319          | 0.8571   |
| 3.6957        | 2.02   | 22   | 0.6454          | 0.8571   |
| 1.7212        | 3.0214 | 30   | 0.2796          | 1.0      |
| 0.6321        | 4.02   | 37   | 0.0587          | 1.0      |
| 0.0861        | 5.0214 | 45   | 0.0120          | 1.0      |
| 0.0166        | 6.02   | 52   | 0.0029          | 1.0      |
| 0.0047        | 7.0214 | 60   | 0.0018          | 1.0      |
| 0.0029        | 8.02   | 67   | 0.0015          | 1.0      |


### Framework versions

- Transformers 4.46.1
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.1