transformers pytorch tensorboard 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-ucf101-subset
  results: []
---

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# videomae-base-finetuned-ucf101-subset

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: 0.4820
- Accuracy: 0.8571

## 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: 148

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.1301        | 0.26  | 38   | 1.9674          | 0.2857   |
| 1.1401        | 1.26  | 76   | 1.0831          | 0.5143   |
| 0.5837        | 2.26  | 114  | 0.6761          | 0.7714   |
| 0.356         | 3.23  | 148  | 0.4820          | 0.8571   |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.0.post101
- Datasets 2.16.1
- Tokenizers 0.13.3
