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---
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-baseline-2
  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-baseline-2

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: 1.4525
- Accuracy: 0.5951

## 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: 16
- eval_batch_size: 16
- 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: 1170

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 1.7757        | 0.0504  | 59   | 1.7544          | 0.3398   |
| 1.4807        | 1.0504  | 118  | 1.7067          | 0.3689   |
| 1.4444        | 2.0504  | 177  | 1.4684          | 0.4320   |
| 1.022         | 3.0504  | 236  | 1.4322          | 0.5388   |
| 0.7796        | 4.0504  | 295  | 1.2440          | 0.5583   |
| 0.5612        | 5.0504  | 354  | 1.3034          | 0.5680   |
| 0.4722        | 6.0504  | 413  | 1.4143          | 0.5728   |
| 0.3215        | 7.0504  | 472  | 1.3449          | 0.5825   |
| 0.2223        | 8.0504  | 531  | 1.3282          | 0.6019   |
| 0.1452        | 9.0504  | 590  | 1.4134          | 0.6068   |
| 0.1771        | 10.0504 | 649  | 1.4489          | 0.6019   |
| 0.0472        | 11.0504 | 708  | 1.5544          | 0.5922   |
| 0.0384        | 12.0504 | 767  | 1.6467          | 0.5874   |


### Framework versions

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