---
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: 0.7609
- Accuracy: 0.9163
- F1: 0.9154

## 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: 22230

### Training results

| Training Loss | Epoch   | Step  | Validation Loss | Accuracy | F1     |
|:-------------:|:-------:|:-----:|:---------------:|:--------:|:------:|
| 0.0           | 0.0333  | 741   | 0.9082          | 0.9070   | 0.9068 |
| 0.5976        | 1.0333  | 1482  | 2.5471          | 0.7302   | 0.7286 |
| 0.1188        | 2.0333  | 2223  | 1.0145          | 0.8698   | 0.8695 |
| 0.0001        | 3.0333  | 2964  | 1.1956          | 0.8465   | 0.8384 |
| 0.5026        | 4.0333  | 3705  | 0.8190          | 0.8651   | 0.8608 |
| 0.0           | 5.0333  | 4446  | 1.1466          | 0.8372   | 0.8377 |
| 0.0           | 6.0333  | 5187  | 1.0804          | 0.8419   | 0.8358 |
| 0.0           | 7.0333  | 5928  | 0.8535          | 0.8930   | 0.8909 |
| 0.0           | 8.0333  | 6669  | 0.6512          | 0.9070   | 0.9070 |
| 0.0001        | 9.0333  | 7410  | 0.8475          | 0.8884   | 0.8887 |
| 0.0001        | 10.0333 | 8151  | 0.7335          | 0.8977   | 0.8972 |
| 0.0           | 11.0333 | 8892  | 0.7774          | 0.9070   | 0.9054 |
| 0.0           | 12.0333 | 9633  | 0.7346          | 0.9116   | 0.9107 |
| 0.0           | 13.0333 | 10374 | 0.7609          | 0.9163   | 0.9154 |
| 0.0           | 14.0333 | 11115 | 0.7560          | 0.9070   | 0.9074 |
| 0.0           | 15.0333 | 11856 | 0.8036          | 0.9163   | 0.9151 |
| 0.0           | 16.0333 | 12597 | 0.7962          | 0.9163   | 0.9151 |
| 0.0           | 17.0333 | 13338 | 0.7821          | 0.9163   | 0.9147 |
| 0.0           | 18.0333 | 14079 | 0.7898          | 0.9163   | 0.9149 |
| 0.0           | 19.0333 | 14820 | 1.0166          | 0.8791   | 0.8748 |
| 0.0           | 20.0333 | 15561 | 0.8697          | 0.8977   | 0.8968 |
| 0.0           | 21.0333 | 16302 | 0.7670          | 0.9023   | 0.9017 |
| 0.0           | 22.0333 | 17043 | 0.7399          | 0.9116   | 0.9107 |
| 0.0           | 23.0333 | 17784 | 0.7458          | 0.9116   | 0.9107 |
| 0.0           | 24.0333 | 18525 | 0.7701          | 0.8977   | 0.8969 |
| 0.0           | 25.0333 | 19266 | 0.7924          | 0.9023   | 0.9014 |
| 0.0           | 26.0333 | 20007 | 0.7955          | 0.9023   | 0.9014 |
| 0.0           | 27.0333 | 20748 | 0.8675          | 0.8977   | 0.8969 |
| 0.0           | 28.0333 | 21489 | 0.8671          | 0.8977   | 0.8969 |
| 0.0           | 29.0333 | 22230 | 0.8665          | 0.8977   | 0.8969 |


### Framework versions

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