---
license: cc-by-nc-4.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-finetuned-ucf101-subset2
  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-subset2

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: 0.4611
- Accuracy: 0.9286

## 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: 4
- eval_batch_size: 4
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0018        | 0.06  | 75   | 0.2489          | 0.9      |
| 0.0033        | 1.06  | 150  | 0.6663          | 0.8429   |
| 0.7225        | 2.06  | 225  | 1.5428          | 0.7143   |
| 0.9709        | 3.06  | 300  | 0.5602          | 0.8571   |
| 0.0012        | 4.06  | 375  | 0.5840          | 0.8857   |
| 0.0471        | 5.06  | 450  | 0.8610          | 0.8429   |
| 0.0008        | 6.06  | 525  | 0.4117          | 0.9      |
| 0.0007        | 7.06  | 600  | 0.4993          | 0.9      |
| 0.0005        | 8.06  | 675  | 0.6722          | 0.8571   |
| 0.0252        | 9.06  | 750  | 0.4827          | 0.8714   |
| 0.0005        | 10.06 | 825  | 0.5150          | 0.9286   |
| 0.0005        | 11.06 | 900  | 0.4033          | 0.9286   |
| 0.0005        | 12.06 | 975  | 0.4546          | 0.9286   |
| 0.0004        | 13.06 | 1050 | 0.4545          | 0.9286   |
| 0.0004        | 14.06 | 1125 | 0.4596          | 0.9286   |
| 0.0005        | 15.06 | 1200 | 0.4611          | 0.9286   |


### Framework versions

- Transformers 4.30.2
- Pytorch 1.8.0
- Datasets 2.13.2
- Tokenizers 0.13.3