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: 0.5225 Accuracy: 0.8756
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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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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.004 | 0.01 | 687 | 0.6479 | 0.8288 |
| 0.0074 | 1.01 | 1374 | 0.6000 | 0.8486 |
| 0.0224 | 2.01 | 2061 | 0.3322 | 0.8988 |
| 0.297 | 3.01 | 2748 | 0.8665 | 0.7984 |
| 0.0564 | 4.01 | 3435 | 1.0001 | 0.8049 |
--- 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-0325_final_lr 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-0325_final_lr 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: 0.5225 - Accuracy: 0.8756 ## 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: 3e-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: 68700 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:-----:|:---------------:|:--------:| | 0.004 | 0.01 | 687 | 0.6479 | 0.8288 | | 0.0074 | 1.01 | 1374 | 0.6000 | 0.8486 | | 0.0224 | 2.01 | 2061 | 0.3322 | 0.8988 | | 0.297 | 3.01 | 2748 | 0.8665 | 0.7984 | | 0.0564 | 4.01 | 3435 | 1.0001 | 0.8049 | | 0.0132 | 5.01 | 4122 | 0.4609 | 0.8798 | | 0.1194 | 6.01 | 4809 | 0.6630 | 0.8560 | | 0.0031 | 7.01 | 5496 | 1.0375 | 0.7967 | | 0.0372 | 8.01 | 6183 | 0.4677 | 0.9021 | | 0.6956 | 9.01 | 6870 | 1.5865 | 0.7243 | | 0.6914 | 10.01 | 7557 | 1.3021 | 0.7819 | | 0.3998 | 11.01 | 8244 | 0.7956 | 0.8568 | | 0.1396 | 12.01 | 8931 | 0.7252 | 0.8807 | | 0.0016 | 13.01 | 9618 | 0.8365 | 0.8634 | | 0.0072 | 14.01 | 10305 | 0.7298 | 0.8486 | | 0.2356 | 15.01 | 10992 | 0.6946 | 0.8617 | | 0.0304 | 16.01 | 11679 | 1.1166 | 0.8313 | | 0.0009 | 17.01 | 12366 | 1.1268 | 0.8329 | | 0.0003 | 18.01 | 13053 | 0.8779 | 0.8535 | | 0.0078 | 19.01 | 13740 | 0.8373 | 0.8617 | | 0.0024 | 20.01 | 14427 | 1.4814 | 0.8041 | | 0.0099 | 21.01 | 15114 | 1.20...
Source context: 5 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo d2o2ji/videomae-base-finetuned-kinetics-0325_final_lr
| 0.0132 | 5.01 | 4122 | 0.4609 | 0.8798 |
| 0.1194 | 6.01 | 4809 | 0.6630 | 0.8560 |
| 0.0031 | 7.01 | 5496 | 1.0375 | 0.7967 |
| 0.0372 | 8.01 | 6183 | 0.4677 | 0.9021 |
| 0.6956 | 9.01 | 6870 | 1.5865 | 0.7243 |
| 0.6914 | 10.01 | 7557 | 1.3021 | 0.7819 |
| 0.3998 | 11.01 | 8244 | 0.7956 | 0.8568 |
| 0.1396 | 12.01 | 8931 | 0.7252 | 0.8807 |
| 0.0016 | 13.01 | 9618 | 0.8365 | 0.8634 |
| 0.0072 | 14.01 | 10305 | 0.7298 | 0.8486 |
| 0.2356 | 15.01 | 10992 | 0.6946 | 0.8617 |
| 0.0304 | 16.01 | 11679 | 1.1166 | 0.8313 |
| 0.0009 | 17.01 | 12366 | 1.1268 | 0.8329 |
| 0.0003 | 18.01 | 13053 | 0.8779 | 0.8535 |
| 0.0078 | 19.01 | 13740 | 0.8373 | 0.8617 |
| 0.0024 | 20.01 | 14427 | 1.4814 | 0.8041 |
| 0.0099 | 21.01 | 15114 | 1.2040 | 0.8412 |
| 0.0188 | 22.01 | 15801 | 1.1281 | 0.8428 |
| 0.0001 | 23.01 | 16488 | 1.0009 | 0.8601 |