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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-collected-dataset
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-collected-dataset
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: 0.2578
- Accuracy: 0.9610
## 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: 14020
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.1001 | 0.1 | 1403 | 0.8989 | 0.7789 |
| 0.2646 | 1.1 | 2806 | 0.5655 | 0.8857 |
| 0.0785 | 2.1 | 4209 | 0.4806 | 0.9053 |
| 0.0001 | 3.1 | 5612 | 0.3706 | 0.9398 |
| 0.054 | 4.1 | 7015 | 0.4007 | 0.9368 |
| 0.0003 | 5.1 | 8418 | 0.2354 | 0.9669 |
| 0.0001 | 6.1 | 9821 | 0.3900 | 0.9474 |
| 0.0003 | 7.1 | 11224 | 0.2667 | 0.9579 |
| 0.0001 | 8.1 | 12627 | 0.2436 | 0.9654 |
| 0.0 | 9.1 | 14020 | 0.2432 | 0.9654 |
### Framework versions
- Transformers 4.39.0
- Pytorch 2.1.0
- Datasets 2.18.0
- Tokenizers 0.15.2