---
library_name: transformers
license: mit
base_model: google/vivit-b-16x2-kinetics400
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ViViT_lsa64_coR
  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_lsa64_coR

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: 0.0008
- 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 2880
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 12.7049       | 0.1   | 288  | 1.3316          | 0.8438   |
| 1.4335        | 1.1   | 576  | 0.0854          | 0.9922   |
| 0.0869        | 2.1   | 864  | 0.0054          | 1.0      |
| 0.0225        | 3.1   | 1152 | 0.0021          | 1.0      |
| 0.0057        | 4.1   | 1440 | 0.0012          | 1.0      |
| 0.0038        | 5.1   | 1728 | 0.0010          | 1.0      |
| 0.0024        | 6.1   | 2016 | 0.0008          | 1.0      |
| 0.0016        | 7.1   | 2304 | 0.0008          | 1.0      |


### Framework versions

- Transformers 4.46.1
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.1