---
license: mit
base_model: google/vivit-b-16x2-kinetics400
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vivit-b-16x2-collected-dataset
  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. -->

# vivit-b-16x2-collected-dataset

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: 0.2578
- Accuracy: 0.9610

## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 14020

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.1001        | 0.1   | 1403  | 0.8989          | 0.7789   |
| 0.2646        | 1.1   | 2806  | 0.5655          | 0.8857   |
| 0.0785        | 2.1   | 4209  | 0.4806          | 0.9053   |
| 0.0001        | 3.1   | 5612  | 0.3706          | 0.9398   |
| 0.054         | 4.1   | 7015  | 0.4007          | 0.9368   |
| 0.0003        | 5.1   | 8418  | 0.2354          | 0.9669   |
| 0.0001        | 6.1   | 9821  | 0.3900          | 0.9474   |
| 0.0003        | 7.1   | 11224 | 0.2667          | 0.9579   |
| 0.0001        | 8.1   | 12627 | 0.2436          | 0.9654   |
| 0.0           | 9.1   | 14020 | 0.2432          | 0.9654   |


### Framework versions

- Transformers 4.39.0
- Pytorch 2.1.0
- Datasets 2.18.0
- Tokenizers 0.15.2