transformers tensorboard safetensors vivit video-classification generated_from_trainer base_model:google/vivit-b-16x2-kinetics400 license:mit endpoints_compatible region:us
---
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
  results: []
---

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

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: 0.0210
- Accuracy: 1.0

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0066        | 0.25  | 300  | 0.0056          | 1.0      |
| 0.001         | 1.25  | 600  | 0.1726          | 0.9730   |
| 0.0005        | 2.25  | 900  | 0.0032          | 1.0      |
| 0.0005        | 3.25  | 1200 | 0.0026          | 1.0      |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
