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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: Loss: 0.3843 Accuracy: 0.8754
Model source
Source description
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:
More information needed
Sources
1 sourceVerified Sep 18
Model artifacts
1 artifactSource excerpts
2 excerptsMore information needed
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.0049 | 0.01 | 687 | 0.6878 | 0.8185 |
| 0.0161 | 1.01 | 1374 | 0.5844 | 0.8088 |
| 0.6614 | 2.01 | 2061 | 0.3424 | 0.8857 |
| 0.5088 | 3.01 | 2748 | 0.9065 | 0.7650 |
| 0.2091 | 4.01 | 3435 | 0.9256 | 0.7626 |
--- 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-0326_final_duration4 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-0326_final_duration4 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: 0.3843 - Accuracy: 0.8754 ## 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: 68700 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:-----:|:---------------:|:--------:| | 0.0049 | 0.01 | 687 | 0.6878 | 0.8185 | | 0.0161 | 1.01 | 1374 | 0.5844 | 0.8088 | | 0.6614 | 2.01 | 2061 | 0.3424 | 0.8857 | | 0.5088 | 3.01 | 2748 | 0.9065 | 0.7650 | | 0.2091 | 4.01 | 3435 | 0.9256 | 0.7626 | | 0.009 | 5.01 | 4122 | 0.7178 | 0.8169 | | 0.29 | 6.01 | 4809 | 0.7745 | 0.7212 | | 0.7553 | 7.01 | 5496 | 0.7524 | 0.8088 | | 0.0055 | 8.01 | 6183 | 0.7167 | 0.8152 | | 0.5588 | 9.01 | 6870 | 1.0367 | 0.7682 | | 0.6595 | 10.01 | 7557 | 1.1490 | 0.7820 | | 0.6293 | 11.01 | 8244 | 1.0725 | 0.7455 | | 0.5309 | 12.01 | 8931 | 0.9115 | 0.8096 | | 0.0211 | 13.01 | 9618 | 1.1408 | 0.7609 | | 0.0024 | 14.01 | 10305 | 1.0798 | 0.8006 | | 0.2369 | 15.01 | 10992 | 1.2863 | 0.7763 | | 0.0193 | 16.01 | 11679 | 1.5129 | 0.7601 | | 0.0014 | 17.01 | 12366 | 1.1389 | 0.7804 | ### 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-0326_final_duration4
| 0.009 | 5.01 | 4122 | 0.7178 | 0.8169 |
| 0.29 | 6.01 | 4809 | 0.7745 | 0.7212 |
| 0.7553 | 7.01 | 5496 | 0.7524 | 0.8088 |
| 0.0055 | 8.01 | 6183 | 0.7167 | 0.8152 |
| 0.5588 | 9.01 | 6870 | 1.0367 | 0.7682 |
| 0.6595 | 10.01 | 7557 | 1.1490 | 0.7820 |
| 0.6293 | 11.01 | 8244 | 1.0725 | 0.7455 |
| 0.5309 | 12.01 | 8931 | 0.9115 | 0.8096 |
| 0.0211 | 13.01 | 9618 | 1.1408 | 0.7609 |
| 0.0024 | 14.01 | 10305 | 1.0798 | 0.8006 |
| 0.2369 | 15.01 | 10992 | 1.2863 | 0.7763 |
| 0.0193 | 16.01 | 11679 | 1.5129 | 0.7601 |
| 0.0014 | 17.01 | 12366 | 1.1389 | 0.7804 |
