Edit model card

videomae-base-finetuned-ucf101-subset

This model is a fine-tuned version of MCG-NJU/videomae-base on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.4025
  • Accuracy: 0.2237

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-06
  • train_batch_size: 8
  • eval_batch_size: 8
  • 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: 480

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.3855 1.0 25 1.3973 0.275
1.4151 2.0 50 1.4034 0.1875
1.4342 3.0 75 1.4028 0.2
1.4189 4.0 100 1.3967 0.1625
1.3925 5.0 125 1.4030 0.2375
1.406 6.0 150 1.3974 0.1875
1.3868 7.0 175 1.4011 0.175
1.3969 8.0 200 1.4019 0.15
1.4233 9.0 225 1.3985 0.2125
1.4011 10.0 250 1.4081 0.25
1.3994 11.0 275 1.4037 0.175
1.3945 12.0 300 1.4094 0.2625
1.3844 13.0 325 1.4050 0.175
1.378 14.0 350 1.4081 0.275
1.3965 15.0 375 1.4095 0.275
1.3982 16.0 400 1.4116 0.275
1.385 17.0 425 1.4114 0.275
1.3735 18.0 450 1.4103 0.275
1.3817 19.0 475 1.4106 0.275
1.3785 19.2 480 1.4106 0.275

Framework versions

  • Transformers 4.44.1
  • Pytorch 2.4.0
  • Datasets 2.19.1
  • Tokenizers 0.19.1
Downloads last month
21
Safetensors
Model size
86.2M 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 Salvatore/videomae-base-finetuned-ucf101-subset

Finetuned
(410)
this model