---
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: ALL_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. -->

# ALL_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: 0.5898
- Accuracy: 0.8233

## 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: 2308

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.6192        | 0.0624  | 144  | 0.6215          | 0.6829   |
| 0.3725        | 1.0624  | 288  | 0.5207          | 0.7530   |
| 0.2718        | 2.0624  | 432  | 0.6017          | 0.7744   |
| 0.1424        | 3.0624  | 576  | 0.5600          | 0.7774   |
| 0.1755        | 4.0624  | 720  | 0.6294          | 0.7896   |
| 0.1333        | 5.0624  | 864  | 0.6707          | 0.7957   |
| 0.0937        | 6.0624  | 1008 | 0.8023          | 0.7927   |
| 0.0692        | 7.0624  | 1152 | 0.7964          | 0.8079   |
| 0.0994        | 8.0624  | 1296 | 0.8140          | 0.7988   |
| 0.028         | 9.0624  | 1440 | 0.8548          | 0.8049   |
| 0.0692        | 10.0624 | 1584 | 0.9202          | 0.8018   |
| 0.027         | 11.0624 | 1728 | 0.9143          | 0.7927   |


### Framework versions

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