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

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: 0.6938
- Accuracy: 0.4672

## 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: 0.001
- 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: 480

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7532        | 0.05  | 25   | 0.7078          | 0.5238   |
| 0.7571        | 1.05  | 50   | 0.7034          | 0.4762   |
| 0.7357        | 2.05  | 75   | 0.7080          | 0.4429   |
| 0.6976        | 3.05  | 100  | 0.7160          | 0.5238   |
| 0.7131        | 4.05  | 125  | 0.6893          | 0.4714   |
| 0.7275        | 5.05  | 150  | 0.8350          | 0.4929   |
| 0.7334        | 6.05  | 175  | 0.7127          | 0.4738   |
| 0.7274        | 7.05  | 200  | 0.7088          | 0.5048   |
| 0.697         | 8.05  | 225  | 0.6911          | 0.5190   |
| 0.7605        | 9.05  | 250  | 0.7296          | 0.4976   |
| 0.7105        | 10.05 | 275  | 0.7100          | 0.4833   |
| 0.6745        | 11.05 | 300  | 0.7271          | 0.4548   |
| 0.7166        | 12.05 | 325  | 0.6955          | 0.5286   |
| 0.6849        | 13.05 | 350  | 0.6981          | 0.4976   |
| 0.6978        | 14.05 | 375  | 0.6976          | 0.4952   |
| 0.6928        | 15.05 | 400  | 0.6941          | 0.5405   |
| 0.7057        | 16.05 | 425  | 0.7022          | 0.5      |
| 0.6842        | 17.05 | 450  | 0.6943          | 0.4738   |
| 0.6824        | 18.05 | 475  | 0.6945          | 0.5167   |
| 0.7065        | 19.01 | 480  | 0.6948          | 0.5143   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2