---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-finetuned-sample_kine
  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-base-finetuned-sample_kine

This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-NJU/videomae-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5079
- Accuracy: 0.8205

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 140

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.7564        | 0.1071 | 15   | 0.6660          | 0.6923   |
| 0.6614        | 1.1071 | 30   | 0.5677          | 0.6923   |
| 0.5941        | 2.1071 | 45   | 0.5079          | 0.8205   |
| 0.3661        | 3.1071 | 60   | 0.6175          | 0.6923   |
| 0.3258        | 4.1071 | 75   | 1.1649          | 0.7436   |
| 0.5887        | 5.1071 | 90   | 0.4697          | 0.7179   |
| 0.3907        | 6.1071 | 105  | 0.9874          | 0.6154   |
| 0.1948        | 7.1071 | 120  | 0.9959          | 0.6667   |
| 0.1424        | 8.1071 | 135  | 1.1357          | 0.6667   |
| 0.2198        | 9.0357 | 140  | 1.1467          | 0.6667   |


### Framework versions

- Transformers 4.43.4
- Pytorch 2.4.1
- Datasets 2.20.0
- Tokenizers 0.19.1