videomae-base-finetuned-movienet-take2-finetuned-movienet-take3

This model is a fine-tuned version of dvs/videomae-base-finetuned-movienet-take2 on an unknown dataset. It achieves the following results on the evaluation set:

• eval_loss: 1.4087
• eval_accuracy: 0.7396
• eval_runtime: 167.2166
• eval_samples_per_second: 1.148
• eval_steps_per_second: 0.144
• epoch: 3.02
• step: 631

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: 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: 0.3
• training_steps: 2960

Framework versions

• Transformers 4.31.0
• Pytorch 2.0.1+cu118
• Datasets 2.14.1
• Tokenizers 0.13.3