---
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_NoCrop_Aug16F-8B16F-GACWDlr
  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_NoCrop_Aug16F-8B16F-GACWDlr

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: 0.8643
- Accuracy: 0.8032

## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 3462

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.6327        | 0.0416  | 144  | 0.6327          | 0.6299   |
| 0.4228        | 1.0416  | 288  | 0.5300          | 0.7464   |
| 0.2855        | 2.0416  | 432  | 0.5658          | 0.7648   |
| 0.2789        | 3.0416  | 576  | 0.5733          | 0.7587   |
| 0.237         | 4.0416  | 720  | 0.7180          | 0.7628   |
| 0.1125        | 5.0416  | 864  | 0.7992          | 0.7710   |
| 0.0921        | 6.0416  | 1008 | 0.8145          | 0.7669   |
| 0.1423        | 7.0416  | 1152 | 0.9354          | 0.7648   |
| 0.1307        | 8.0416  | 1296 | 0.9036          | 0.7648   |
| 0.0479        | 9.0416  | 1440 | 1.1271          | 0.7730   |
| 0.0724        | 10.0416 | 1584 | 1.0805          | 0.7669   |
| 0.1424        | 11.0416 | 1728 | 1.0949          | 0.7669   |
| 0.0577        | 12.0416 | 1872 | 1.1183          | 0.7730   |
| 0.1258        | 13.0416 | 2016 | 1.0614          | 0.7914   |
| 0.0271        | 14.0416 | 2160 | 1.1381          | 0.7771   |
| 0.0557        | 15.0416 | 2304 | 1.2154          | 0.7587   |
| 0.054         | 16.0416 | 2448 | 1.1568          | 0.7710   |
| 0.1001        | 17.0416 | 2592 | 1.1639          | 0.7853   |
| 0.0401        | 18.0416 | 2736 | 1.1892          | 0.7812   |


### Framework versions

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