---
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: RALL_RGBCROP_Aug16F-cosine_with_restarts
  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. -->

# RALL_RGBCROP_Aug16F-cosine_with_restarts

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: 0.4225
- Accuracy: 0.8494

## 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-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 3462

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.4395        | 0.0835 | 289  | 0.5305          | 0.7239   |
| 0.2409        | 1.0835 | 578  | 0.5012          | 0.8016   |
| 0.0269        | 2.0835 | 867  | 0.6809          | 0.8160   |
| 0.0086        | 3.0835 | 1156 | 0.8971          | 0.7894   |
| 0.0008        | 4.0835 | 1445 | 0.9614          | 0.8160   |
| 0.0004        | 5.0835 | 1734 | 1.0207          | 0.8160   |
| 0.0004        | 6.0835 | 2023 | 1.0934          | 0.8139   |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1