---
library_name: transformers
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: []
---

<!-- 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

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: 0.3320
- Accuracy: 0.9290

## 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
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 600
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 2.3375        | 0.0617  | 37   | 2.1297          | 0.3      |
| 1.7263        | 1.0625  | 75   | 1.4907          | 0.4714   |
| 0.675         | 2.0617  | 112  | 0.6070          | 0.8714   |
| 0.3702        | 3.0625  | 150  | 0.4089          | 0.8571   |
| 0.205         | 4.0617  | 187  | 0.4285          | 0.8286   |
| 0.3209        | 5.0625  | 225  | 0.2749          | 0.8714   |
| 0.1253        | 6.0617  | 262  | 0.0571          | 0.9857   |
| 0.1052        | 7.0625  | 300  | 0.2550          | 0.9429   |
| 0.1586        | 8.0617  | 337  | 0.1588          | 0.9429   |
| 0.0498        | 9.0625  | 375  | 0.0736          | 0.9857   |
| 0.0958        | 10.0617 | 412  | 0.0911          | 0.9571   |
| 0.1095        | 11.0625 | 450  | 0.0448          | 0.9857   |
| 0.0065        | 12.0617 | 487  | 0.0734          | 0.9857   |
| 0.0019        | 13.0625 | 525  | 0.0603          | 0.9857   |
| 0.0018        | 14.0617 | 562  | 0.0607          | 0.9857   |
| 0.0018        | 15.0625 | 600  | 0.0634          | 0.9857   |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.0.1+cu117
- Datasets 3.2.0
- Tokenizers 0.20.3