---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base-finetuned-kinetics
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-finetuned-kinetics-finetuned-right-hand-conflab-v7
  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-kinetics-finetuned-right-hand-conflab-v7

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: 1.6074
- Accuracy: 0.6195

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 1755

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.3647        | 0.0672  | 118  | 1.5877          | 0.5971   |
| 0.2213        | 1.0672  | 236  | 1.6058          | 0.6117   |
| 0.19          | 2.0672  | 354  | 1.6941          | 0.5728   |
| 0.061         | 3.0672  | 472  | 1.7403          | 0.5922   |
| 0.0512        | 4.0672  | 590  | 1.7683          | 0.5971   |
| 0.0393        | 5.0672  | 708  | 1.7420          | 0.6262   |
| 0.0219        | 6.0672  | 826  | 1.7741          | 0.6019   |
| 0.0363        | 7.0672  | 944  | 1.7825          | 0.6117   |
| 0.0457        | 8.0672  | 1062 | 1.8103          | 0.6019   |
| 0.0201        | 9.0672  | 1180 | 1.8303          | 0.6019   |
| 0.0325        | 10.0672 | 1298 | 1.8135          | 0.6165   |
| 0.049         | 11.0672 | 1416 | 1.8364          | 0.6214   |
| 0.0077        | 12.0672 | 1534 | 1.8431          | 0.6165   |
| 0.0088        | 13.0672 | 1652 | 1.8508          | 0.6165   |
| 0.0818        | 14.0587 | 1755 | 1.8490          | 0.6117   |


### Framework versions

- Transformers 4.41.0
- Pytorch 1.12.0+cu116
- Datasets 2.19.1
- Tokenizers 0.19.1