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: 1.1708 Accuracy: 0.7595
Fuente del modelo
Descripción de la fuente
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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Fuentes
1 fuenteVerificado 18 sept
Artefactos del modelo
1 artefactoExtractos de fuentes
2 extractosMore information needed
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.4251 | 0.0100 | 631 | 0.7287 | 0.8076 |
| 0.5829 | 1.0100 | 1262 | 0.7866 | 0.7696 |
| 0.3161 | 2.0100 | 1893 | 0.4666 | 0.8191 |
| 0.1667 | 3.0100 | 2524 | 1.3251 | 0.7493 |
| 0.0019 | 4.0100 | 3155 | 1.3841 | 0.7485 |
--- 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-0404_final_45sec 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-0404_final_45sec 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: 1.1708 - Accuracy: 0.7595 ## 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: 63000 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-------:|:-----:|:---------------:|:--------:| | 0.4251 | 0.0100 | 631 | 0.7287 | 0.8076 | | 0.5829 | 1.0100 | 1262 | 0.7866 | 0.7696 | | 0.3161 | 2.0100 | 1893 | 0.4666 | 0.8191 | | 0.1667 | 3.0100 | 2524 | 1.3251 | 0.7493 | | 0.0019 | 4.0100 | 3155 | 1.3841 | 0.7485 | | 0.006 | 5.0100 | 3786 | 0.7565 | 0.8358 | | 0.0088 | 6.0100 | 4417 | 1.3582 | 0.7767 | | 0.0026 | 7.0100 | 5048 | 1.2738 | 0.7652 | | 0.0015 | 8.0100 | 5679 | 1.0358 | 0.8173 | | 0.24 | 9.0100 | 6310 | 0.9473 | 0.8350 | | 0.0065 | 10.0100 | 6941 | 1.2006 | 0.7696 | | 0.0004 | 11.0100 | 7572 | 1.2525 | 0.7891 | | 0.0003 | 12.0100 | 8203 | 2.1669 | 0.7017 | | 0.0004 | 13.0100 | 8834 | 1.5847 | 0.7696 | | 0.0053 | 14.0100 | 9465 | 0.8446 | 0.8420 | | 0.0017 | 15.0100 | 10096 | 1.2059 | 0.8076 | | 0.0019 | 16.0100 | 10727 | 1.6806 | 0.7432 | | 0.0028 | 17.0100 | 11358 | 1.1255 | 0.8138 | | 0.737 | 18.0100 | 11989 | 1.6861 | 0.7626 | | 0.0001 | 19.0100 | 12620 | 1.2263 | 0.8226 | | 0.0012 | 20.0100 | 13251 | 1....
Source context: 3 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo d2o2ji/videomae-base-finetuned-kinetics-0404_final_45sec
| 0.006 | 5.0100 | 3786 | 0.7565 | 0.8358 |
| 0.0088 | 6.0100 | 4417 | 1.3582 | 0.7767 |
| 0.0026 | 7.0100 | 5048 | 1.2738 | 0.7652 |
| 0.0015 | 8.0100 | 5679 | 1.0358 | 0.8173 |
| 0.24 | 9.0100 | 6310 | 0.9473 | 0.8350 |
| 0.0065 | 10.0100 | 6941 | 1.2006 | 0.7696 |
| 0.0004 | 11.0100 | 7572 | 1.2525 | 0.7891 |
| 0.0003 | 12.0100 | 8203 | 2.1669 | 0.7017 |
| 0.0004 | 13.0100 | 8834 | 1.5847 | 0.7696 |
| 0.0053 | 14.0100 | 9465 | 0.8446 | 0.8420 |
| 0.0017 | 15.0100 | 10096 | 1.2059 | 0.8076 |
| 0.0019 | 16.0100 | 10727 | 1.6806 | 0.7432 |
| 0.0028 | 17.0100 | 11358 | 1.1255 | 0.8138 |
| 0.737 | 18.0100 | 11989 | 1.6861 | 0.7626 |
| 0.0001 | 19.0100 | 12620 | 1.2263 | 0.8226 |
| 0.0012 | 20.0100 | 13251 | 1.7637 | 0.7555 |
| 0.1868 | 21.0100 | 13882 | 1.5043 | 0.7988 |
| 0.0003 | 22.0100 | 14513 | 1.7795 | 0.7838 |
| 0.0033 | 23.0100 | 15144 | 1.3303 | 0.8147 |
| 0.1839 | 24.0100 | 15775 | 1.5371 | 0.7882 |
| 0.0019 | 25.0100 | 16406 | 1.6585 | 0.7811 |
| 0.0001 | 26.0100 | 17037 | 1.2823 | 0.8111 |
| 0.0151 | 27.0100 | 17668 | 1.1360 | 0.8376 |
| 0.0001 | 28.0100 | 18299 | 1.4864 | 0.8041 |
| 0.0008 | 29.0100 | 18930 | 1.5519 | 0.7988 |