---
license: cc-by-nc-4.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-finetuned-engine-subset-20230310
  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-engine-subset-20230310

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: 0.4958
- Accuracy: 0.85

## 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: 6
- eval_batch_size: 6
- 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: 600

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.5947        | 0.05  | 31   | 2.5383          | 0.15     |
| 2.4195        | 1.05  | 62   | 2.5108          | 0.15     |
| 2.2476        | 2.05  | 93   | 2.0533          | 0.225    |
| 1.9449        | 3.05  | 124  | 2.0719          | 0.2375   |
| 1.5724        | 4.05  | 155  | 1.4756          | 0.475    |
| 1.395         | 5.05  | 186  | 1.2884          | 0.5      |
| 1.0822        | 6.05  | 217  | 1.0679          | 0.575    |
| 1.0635        | 7.05  | 248  | 0.8040          | 0.7      |
| 0.8707        | 8.05  | 279  | 0.9334          | 0.525    |
| 0.7042        | 9.05  | 310  | 0.6477          | 0.75     |
| 0.6543        | 10.05 | 341  | 0.6963          | 0.7375   |
| 0.6807        | 11.05 | 372  | 0.4958          | 0.85     |
| 0.4924        | 12.05 | 403  | 0.6374          | 0.775    |
| 0.4822        | 13.05 | 434  | 0.6145          | 0.75     |
| 0.4878        | 14.05 | 465  | 0.6274          | 0.7625   |
| 0.4442        | 15.05 | 496  | 0.4231          | 0.85     |
| 0.2739        | 16.05 | 527  | 0.4999          | 0.85     |
| 0.3514        | 17.05 | 558  | 0.4639          | 0.8375   |
| 0.4158        | 18.05 | 589  | 0.4291          | 0.85     |
| 0.2689        | 19.02 | 600  | 0.4294          | 0.85     |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.12.1+cu113
- Datasets 2.10.1
- Tokenizers 0.13.2