---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-finetuned-ucf101-subset-SBDtoy
  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-ucf101-subset-SBDtoy

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: 1.8346
- Accuracy: 0.6275

## 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: 2
- eval_batch_size: 2
- 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: 1200

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7634        | 0.03  | 41   | 0.6320          | 0.5882   |
| 0.7445        | 1.03  | 82   | 1.4198          | 0.5686   |
| 0.4931        | 2.03  | 123  | 1.3689          | 0.5686   |
| 0.7206        | 3.03  | 164  | 1.3282          | 0.5882   |
| 0.735         | 4.03  | 205  | 2.0849          | 0.5686   |
| 1.769         | 5.03  | 246  | 1.0332          | 0.6078   |
| 0.9494        | 6.03  | 287  | 2.1307          | 0.6078   |
| 0.3857        | 7.03  | 328  | 2.5985          | 0.6078   |
| 0.3639        | 8.03  | 369  | 2.2300          | 0.6078   |
| 0.6456        | 9.03  | 410  | 1.8992          | 0.6078   |
| 0.9483        | 10.03 | 451  | 1.9556          | 0.6078   |
| 0.4518        | 11.03 | 492  | 1.8346          | 0.6275   |
| 0.9109        | 12.03 | 533  | 1.9937          | 0.6078   |
| 0.5441        | 13.03 | 574  | 1.4013          | 0.6078   |
| 0.4035        | 14.03 | 615  | 1.9078          | 0.6078   |
| 0.1713        | 15.03 | 656  | 2.0803          | 0.5882   |
| 0.0542        | 16.03 | 697  | 2.5432          | 0.6078   |
| 0.3084        | 17.03 | 738  | 2.5753          | 0.6078   |
| 0.2476        | 18.03 | 779  | 2.4253          | 0.6275   |
| 0.006         | 19.03 | 820  | 2.4320          | 0.6078   |
| 0.0021        | 20.03 | 861  | 2.7182          | 0.6078   |
| 0.008         | 21.03 | 902  | 2.7711          | 0.5882   |
| 0.0011        | 22.03 | 943  | 2.8089          | 0.5882   |
| 0.7546        | 23.03 | 984  | 2.8142          | 0.6078   |
| 0.0006        | 24.03 | 1025 | 2.8796          | 0.6078   |
| 0.0008        | 25.03 | 1066 | 2.8486          | 0.6078   |
| 0.1745        | 26.03 | 1107 | 2.8475          | 0.6078   |
| 0.5421        | 27.03 | 1148 | 2.8462          | 0.6078   |
| 0.1233        | 28.03 | 1189 | 2.8324          | 0.6078   |
| 0.1298        | 29.01 | 1200 | 2.8332          | 0.6078   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.0.1
- Datasets 2.18.0
- Tokenizers 0.15.2