---
license: mit
base_model: google/vivit-b-16x2-kinetics400
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vivit-b-16x2-kinetics400_training_O_OM_0519
  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-kinetics400_training_O_OM_0519

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: 1.1012
- Accuracy: 0.815

## 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: 3000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.9097        | 0.1   | 300  | 0.9219          | 0.64     |
| 0.0229        | 1.1   | 600  | 0.7215          | 0.83     |
| 0.0019        | 2.1   | 900  | 0.9705          | 0.815    |
| 0.2377        | 3.1   | 1200 | 1.0544          | 0.815    |
| 0.0002        | 4.1   | 1500 | 1.1033          | 0.8      |
| 0.0003        | 5.1   | 1800 | 1.0511          | 0.82     |
| 0.0002        | 6.1   | 2100 | 1.0354          | 0.805    |
| 0.0033        | 7.1   | 2400 | 1.1037          | 0.81     |
| 0.0002        | 8.1   | 2700 | 1.0985          | 0.815    |
| 0.0002        | 9.1   | 3000 | 1.1012          | 0.815    |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1