student_videomobilevit_dist_kl_temp_1_alpha_0.6_teacher_mvit_v2_s_RWF2000

This model is a fine-tuned version of Video-MobileVit on an Real World Fight 2000 (RWF2000). It achieves the following results on the evaluation set:

  • Loss: 0.6388
  • Accuracy: 0.7488
  • F1: 0.7471
  • Precision: 0.7555

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: 1e-05
  • train_batch_size: 20
  • eval_batch_size: 20
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 180
  • training_steps: 1800
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy F1 Precision
0.5041 2.02 180 0.4884 0.7625 0.7604 0.7721
0.3788 4.04 360 0.4183 0.8094 0.8091 0.8114
0.3226 7.02 540 0.4292 0.8187 0.8175 0.8274
0.2425 9.04 720 0.4234 0.8094 0.8073 0.8231
0.243 12.02 900 0.3590 0.8313 0.8311 0.8325
0.1914 14.04 1080 0.3708 0.8375 0.8373 0.8388
0.1832 17.02 1260 0.3755 0.8469 0.8469 0.8470
0.1624 19.04 1440 0.4323 0.8375 0.8366 0.8453

Framework versions

  • Transformers 4.45.2
  • Pytorch 2.0.1+cu118
  • Datasets 3.0.1
  • Tokenizers 0.20.0
Downloads last month
11
Safetensors
Model size
22M params
Tensor type
F32
·
Inference API
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for DanJoshua/student_videomobilevit_dist_kl_temp_1_alpha_0.6_teacher_mvit_v2_s_RWF2000

Finetuned
(1)
this model

Dataset used to train DanJoshua/student_videomobilevit_dist_kl_temp_1_alpha_0.6_teacher_mvit_v2_s_RWF2000