ViViT_LSA64_SR_6 / README.md
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metadata
library_name: transformers
license: mit
base_model: google/vivit-b-16x2-kinetics400
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: ViViT_LSA64_SR_6
    results: []

ViViT_LSA64_SR_6

This model is a fine-tuned version of google/vivit-b-16x2-kinetics400 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0190
  • Accuracy: 0.9961
  • Precision: 0.9969
  • Recall: 0.9961
  • F1: 0.9960

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: 8640
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision Recall F1
15.7817 0.0333 288 2.8824 0.4609 0.5309 0.4609 0.4307
4.7558 1.0333 576 0.5582 0.9492 0.9586 0.9492 0.9470
0.5173 2.0333 864 0.0999 0.9805 0.9854 0.9805 0.9798
0.1244 3.0333 1152 0.0102 1.0 1.0 1.0 1.0
0.0043 4.0333 1440 0.0265 0.9922 0.9938 0.9922 0.9921
0.021 5.0333 1728 0.0200 0.9922 0.9938 0.9922 0.9921
0.0014 6.0333 2016 0.0012 1.0 1.0 1.0 1.0
0.0414 7.0333 2304 0.0075 0.9961 0.9969 0.9961 0.9960
0.0386 8.0333 2592 0.0190 0.9961 0.9969 0.9961 0.9960

Framework versions

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