transformers pytorch videomae video-classification generated_from_trainer base_model:MCG-NJU/videomae-base license:cc-by-nc-4.0 endpoints_compatible region:us
---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-finetuned-gemep-epochs25
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# videomae-base-finetuned-gemep-epochs25

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: 0.4373
- Accuracy: 0.9123

## 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: 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: 1350

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.7648        | 0.04  | 54   | 1.7458          | 0.2698   |
| 1.6977        | 1.04  | 108  | 1.5724          | 0.2698   |
| 1.5208        | 2.04  | 162  | 1.5350          | 0.2857   |
| 1.39          | 3.04  | 216  | 1.4793          | 0.4286   |
| 1.3546        | 4.04  | 270  | 1.7122          | 0.2857   |
| 0.9587        | 5.04  | 324  | 1.4137          | 0.3492   |
| 1.0259        | 6.04  | 378  | 1.2302          | 0.6190   |
| 0.7292        | 7.04  | 432  | 1.4772          | 0.3810   |
| 0.6499        | 8.04  | 486  | 1.0864          | 0.5873   |
| 0.5417        | 9.04  | 540  | 1.4085          | 0.4603   |
| 0.5073        | 10.04 | 594  | 1.5436          | 0.5556   |
| 0.5052        | 11.04 | 648  | 1.2583          | 0.6190   |
| 0.419         | 12.04 | 702  | 1.1921          | 0.6349   |
| 0.2677        | 13.04 | 756  | 1.0662          | 0.6825   |
| 0.1601        | 14.04 | 810  | 0.7688          | 0.7143   |
| 0.1784        | 15.04 | 864  | 1.2971          | 0.6508   |
| 0.1338        | 16.04 | 918  | 0.9488          | 0.7937   |
| 0.0875        | 17.04 | 972  | 1.0488          | 0.7619   |
| 0.0748        | 18.04 | 1026 | 0.9617          | 0.8095   |
| 0.0973        | 19.04 | 1080 | 1.0684          | 0.7460   |
| 0.0443        | 20.04 | 1134 | 1.0433          | 0.7778   |
| 0.0787        | 21.04 | 1188 | 0.8444          | 0.8254   |
| 0.0035        | 22.04 | 1242 | 1.1333          | 0.7778   |
| 0.0033        | 23.04 | 1296 | 0.9644          | 0.8095   |
| 0.0686        | 24.04 | 1350 | 0.9196          | 0.8254   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.0
- Datasets 2.12.0
- Tokenizers 0.13.3
