---
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
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# RALL_NoCrop_Aug16F-8B16F

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: 1.0091
- Accuracy: 0.7751

## 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: 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: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 4616

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.4546        | 0.0626 | 289  | 0.5467          | 0.7566   |
| 0.2899        | 1.0626 | 578  | 0.7078          | 0.7157   |
| 0.1739        | 2.0626 | 867  | 0.8752          | 0.7771   |
| 0.1227        | 3.0626 | 1156 | 0.7922          | 0.7710   |
| 0.1752        | 4.0626 | 1445 | 1.0169          | 0.7812   |
| 0.1473        | 5.0626 | 1734 | 0.9909          | 0.7587   |
| 0.2319        | 6.0626 | 2023 | 1.3500          | 0.7444   |
| 0.0379        | 7.0626 | 2312 | 1.1374          | 0.7771   |
| 0.0109        | 8.0626 | 2601 | 1.2297          | 0.7628   |
| 0.0514        | 9.0626 | 2890 | 1.2982          | 0.7751   |


### Framework versions

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