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---
license: mit
base_model: google/vivit-b-16x2-kinetics400
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vivit-b-16x2-kinetics400-0511-mediapipe
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-kinetics400-0511-mediapipe
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: 0.9073
- Accuracy: 0.82
## 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: 1400
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.2076 | 0.1 | 140 | 2.4158 | 0.15 |
| 1.184 | 1.1 | 280 | 1.2269 | 0.6 |
| 0.6475 | 2.1 | 420 | 0.7247 | 0.76 |
| 0.3137 | 3.1 | 560 | 0.7076 | 0.78 |
| 0.0356 | 4.1 | 700 | 0.7347 | 0.82 |
| 0.0017 | 5.1 | 840 | 0.8888 | 0.83 |
| 0.0007 | 6.1 | 980 | 0.9464 | 0.8 |
| 0.265 | 7.1 | 1120 | 1.0068 | 0.8 |
| 0.0012 | 8.1 | 1260 | 0.8982 | 0.82 |
| 0.0007 | 9.1 | 1400 | 0.9073 | 0.82 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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