This model is a fine-tuned version of MCG-NJU/videomae-base-finetuned-kinetics on an unknown dataset. It achieves the following results on the evaluation set: Loss: 0.5217 Accuracy: 0.8412
Modellquelle
Quellenbeschreibung
This model is a fine-tuned version of MCG-NJU/videomae-base-finetuned-kinetics on an unknown dataset. It achieves the following results on the evaluation set:
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Quellen
1 QuelleVerifiziert 18. Sept.
Modellartefakte
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2 AuszügeMore information needed
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.0025 | 0.0087 | 560 | 0.3472 | 0.8818 |
| 0.071 | 1.0087 | 1120 | 0.4068 | 0.8745 |
| 0.0045 | 2.0087 | 1680 | 0.6408 | 0.8409 |
| 0.8664 | 3.0087 | 2240 | 0.7236 | 0.8118 |
| 0.008 | 4.0087 | 2800 | 0.5544 | 0.8436 |
--- library_name: transformers license: cc-by-nc-4.0 base_model: MCG-NJU/videomae-base-finetuned-kinetics tags: - generated_from_trainer metrics: - accuracy model-index: - name: videomae-base-finetuned-kinetics-0407_final_5sec_bbox 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-kinetics-0407_final_5sec_bbox This model is a fine-tuned version of [MCG-NJU/videomae-base-finetuned-kinetics](https://huggingface.co/MCG-NJU/videomae-base-finetuned-kinetics) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.5217 - Accuracy: 0.8412 ## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.05 - training_steps: 64400 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-------:|:----:|:---------------:|:--------:| | 0.0025 | 0.0087 | 560 | 0.3472 | 0.8818 | | 0.071 | 1.0087 | 1120 | 0.4068 | 0.8745 | | 0.0045 | 2.0087 | 1680 | 0.6408 | 0.8409 | | 0.8664 | 3.0087 | 2240 | 0.7236 | 0.8118 | | 0.008 | 4.0087 | 2800 | 0.5544 | 0.8436 | | 0.0253 | 5.0087 | 3360 | 0.5049 | 0.8755 | | 0.1241 | 6.0087 | 3920 | 1.8205 | 0.6645 | | 0.0154 | 7.0087 | 4480 | 1.0555 | 0.7545 | | 0.0874 | 8.0087 | 5040 | 0.6577 | 0.8564 | | 1.3739 | 9.0087 | 5600 | 1.6253 | 0.6809 | | 0.0012 | 10.0087 | 6160 | 1.0850 | 0.7673 | | 0.0005 | 11.0087 | 6720 | 1.0242 | 0.7809 | | 0.9725 | 12.0087 | 7280 | 1.5750 | 0.73 | | 0.0007 | 13.0087 | 7840 | 1.5301 | 0.7518 | | 0.2368 | 14.0087 | 8400 | 1.0420 | 0.8209 | | 0.0001 | 15.0087 | 8960 | 1.4675 | 0.7736 | ### Framework versions - Transformers 4.48.0 - Pytorch 2.5.1+cu124 - Datasets 3.2.0 - Tokenizers 0.21.0
Source context: 2 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo d2o2ji/videomae-base-finetuned-kinetics-0407_final_5sec_bbox
| 0.0253 | 5.0087 | 3360 | 0.5049 | 0.8755 |
| 0.1241 | 6.0087 | 3920 | 1.8205 | 0.6645 |
| 0.0154 | 7.0087 | 4480 | 1.0555 | 0.7545 |
| 0.0874 | 8.0087 | 5040 | 0.6577 | 0.8564 |
| 1.3739 | 9.0087 | 5600 | 1.6253 | 0.6809 |
| 0.0012 | 10.0087 | 6160 | 1.0850 | 0.7673 |
| 0.0005 | 11.0087 | 6720 | 1.0242 | 0.7809 |
| 0.9725 | 12.0087 | 7280 | 1.5750 | 0.73 |
| 0.0007 | 13.0087 | 7840 | 1.5301 | 0.7518 |
| 0.2368 | 14.0087 | 8400 | 1.0420 | 0.8209 |
| 0.0001 | 15.0087 | 8960 | 1.4675 | 0.7736 |