Timesformer Base K400 Finetuned CricketV5.0

--- library_name: transformers license: cc-by-nc-4.0 base_model: facebook/timesformer-base-finetuned-k400 tags: - generated_from_trainer model-index: - name: timesformer-base-k400-finetuned-cricketV5.0 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. --> # timesformer-base-k400-finetuned-cricketV5.0 This model is a fine-tuned version of [facebook/timesformer-base-finetuned-k400](https://huggingface.co/facebook/timesformer-base-finetuned-k400) on an unknown dataset. It achieves the following results on the evaluation set: - eval_loss: 1.6617 - eval_accuracy: 0.4387 - eval_acc_hook: 0.24 - eval_acc_sweep: 0.8077 - eval_acc_pull: 0.5385 - eval_runtime: 71.14 - eval_samples_per_second: 4.358 - eval_steps_per_second: 1.096 - epoch: 32.0138 - step: 650 ## 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: 4 - seed: 42 - gradient_accumulation_steps: 8 - total_train_batch_size: 64 - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 100 - training_steps: 800 - label_smoothing_factor: 0.05 ### Framework versions - Transformers 5.3.0 - Pytorch 2.10.0 - Datasets 4.7.0 - Tokenizers 0.22.2

Source context: 14 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo SaurabhShashank/timesformer-base-k400-finetuned-cricketV5.0

Source context: 4 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo SaurabhShashank/timesformer-base-k400-finetuned-cricketV5.0