---
license: mit
base_model: google/vivit-b-16x2-kinetics400
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: vivit-surf-analytics-runpod
  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-surf-analytics-runpod

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: 0.7570
- Accuracy: 0.9023
- F1: 0.9016

## 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: 741

### Training results

| Training Loss | Epoch   | Step  | Accuracy | F1     | Validation Loss |
|:-------------:|:-------:|:-----:|:--------:|:------:|:---------------:|
| 1.3533        | 0.05    | 741   | 0.8393   | 0.8382 | 0.7031          |
| 0.0028        | 1.05    | 1482  | 0.8482   | 0.8460 | 0.7500          |
| 0.0021        | 2.05    | 2223  | 0.8839   | 0.8821 | 0.5604          |
| 0.0002        | 3.05    | 2964  | 0.9018   | 0.9001 | 0.3880          |
| 0.0001        | 4.05    | 3705  | 0.9286   | 0.9284 | 0.4309          |
| 0.0001        | 5.05    | 4446  | 0.9107   | 0.9105 | 0.7365          |
| 0.8987        | 6.05    | 5187  | 0.8393   | 0.8294 | 0.9310          |
| 0.4888        | 7.05    | 5928  | 0.875    | 0.8703 | 0.8563          |
| 0.0001        | 8.05    | 6669  | 0.8929   | 0.8894 | 0.6909          |
| 0.0018        | 9.05    | 7410  | 0.8929   | 0.8917 | 0.9169          |
| 0.0           | 10.05   | 8151  | 0.8929   | 0.8928 | 0.6104          |
| 0.0           | 11.05   | 8892  | 0.9196   | 0.9207 | 0.6125          |
| 0.0           | 12.05   | 9633  | 0.9286   | 0.9281 | 0.5644          |
| 0.0           | 13.05   | 10374 | 0.9286   | 0.9286 | 0.5062          |
| 0.0           | 14.05   | 11115 | 0.9375   | 0.9373 | 0.5186          |
| 0.0           | 15.0013 | 11116 | 0.7569   | 0.9023 | 0.9016          |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1