Videomae Base Finetuned Movienet Take2 Finetuned Movienet Take3

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

--- license: cc-by-nc-4.0 base_model: dvs/videomae-base-finetuned-movienet-take2 tags: - generated_from_trainer model-index: - name: videomae-base-finetuned-movienet-take2-finetuned-movienet-take3 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. --> # videomae-base-finetuned-movienet-take2-finetuned-movienet-take3 This model is a fine-tuned version of [dvs/videomae-base-finetuned-movienet-take2](https://huggingface.co/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