---
license: mit
base_model: google/vivit-b-16x2-kinetics400
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vivit-b-16x2-kinetics400-finetuned-ucf101-subset-new
  results: []
datasets:
- sayakpaul/ucf101-subset
pipeline_tag: video-classification
---

<!-- 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. -->

# vivit-b-16x2-kinetics400-finetuned-ucf101-subset-new

This model is a fine-tuned version of [google/vivit-b-16x2-kinetics400](https://huggingface.co/google/vivit-b-16x2-kinetics400) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0228
- Accuracy: 0.9933

## 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: 1
- eval_batch_size: 1
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.027         | 0.25  | 300  | 0.0306          | 1.0      |
| 0.0036        | 1.25  | 600  | 0.0418          | 0.9799   |
| 0.019         | 2.25  | 900  | 0.0046          | 1.0      |
| 0.001         | 3.25  | 1200 | 0.0228          | 0.9933   |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.0.1+cu117
- Datasets 2.21.0
- Tokenizers 0.19.1