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: 0.8258 Accuracy: 0.7900
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:
More information needed
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 |
|---|---|---|---|---|
| 0.0811 | 0.0100 | 622 | 0.3101 | 0.8648 |
| 0.0068 | 1.0100 | 1244 | 0.5977 | 0.8141 |
| 0.0011 | 2.0100 | 1866 | 0.7745 | 0.8203 |
| 0.0276 | 3.0100 | 2488 | 0.6727 | 0.8541 |
| 0.6154 | 4.0100 | 3110 | 0.6580 | 0.8399 |
--- 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-0403_final_only5sec_retry 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-0403_final_only5sec_retry 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: 0.8258 - Accuracy: 0.7900 ## 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: 62100 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-------:|:-----:|:---------------:|:--------:| | 0.0811 | 0.0100 | 622 | 0.3101 | 0.8648 | | 0.0068 | 1.0100 | 1244 | 0.5977 | 0.8141 | | 0.0011 | 2.0100 | 1866 | 0.7745 | 0.8203 | | 0.0276 | 3.0100 | 2488 | 0.6727 | 0.8541 | | 0.6154 | 4.0100 | 3110 | 0.6580 | 0.8399 | | 0.1148 | 5.0100 | 3732 | 0.7695 | 0.8274 | | 0.0053 | 6.0100 | 4354 | 0.8514 | 0.7945 | | 0.0007 | 7.0100 | 4976 | 0.7208 | 0.8238 | | 0.0014 | 8.0100 | 5598 | 1.3792 | 0.7375 | | 0.0027 | 9.0100 | 6220 | 0.3791 | 0.8959 | | 1.163 | 10.0100 | 6842 | 1.3893 | 0.7456 | | 0.0178 | 11.0100 | 7464 | 1.1741 | 0.7820 | | 0.009 | 12.0100 | 8086 | 0.6941 | 0.8470 | | 0.004 | 13.0100 | 8708 | 0.9689 | 0.8274 | | 1.0064 | 14.0100 | 9330 | 0.7809 | 0.8230 | | 0.0003 | 15.0100 | 9952 | 1.1843 | 0.7918 | | 0.0012 | 16.0100 | 10574 | 0.6599 | 0.8594 | | 0.0395 | 17.0100 | 11196 | 0.6761 | 0.8799 | | 0.0005 | 18.0100 | 11818 | 1.0149 | 0.8158 | | 0.7313 | 19.0100 | 12440 | 1.3613 | 0.7811 | | 0.0004 | 20...
Source context: 3 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo d2o2ji/videomae-base-finetuned-kinetics-0403_final_only5sec_retry
| 0.1148 | 5.0100 | 3732 | 0.7695 | 0.8274 |
| 0.0053 | 6.0100 | 4354 | 0.8514 | 0.7945 |
| 0.0007 | 7.0100 | 4976 | 0.7208 | 0.8238 |
| 0.0014 | 8.0100 | 5598 | 1.3792 | 0.7375 |
| 0.0027 | 9.0100 | 6220 | 0.3791 | 0.8959 |
| 1.163 | 10.0100 | 6842 | 1.3893 | 0.7456 |
| 0.0178 | 11.0100 | 7464 | 1.1741 | 0.7820 |
| 0.009 | 12.0100 | 8086 | 0.6941 | 0.8470 |
| 0.004 | 13.0100 | 8708 | 0.9689 | 0.8274 |
| 1.0064 | 14.0100 | 9330 | 0.7809 | 0.8230 |
| 0.0003 | 15.0100 | 9952 | 1.1843 | 0.7918 |
| 0.0012 | 16.0100 | 10574 | 0.6599 | 0.8594 |
| 0.0395 | 17.0100 | 11196 | 0.6761 | 0.8799 |
| 0.0005 | 18.0100 | 11818 | 1.0149 | 0.8158 |
| 0.7313 | 19.0100 | 12440 | 1.3613 | 0.7811 |
| 0.0004 | 20.0100 | 13062 | 0.9187 | 0.8390 |
| 1.638 | 21.0100 | 13684 | 0.8302 | 0.8692 |
| 0.0002 | 22.0100 | 14306 | 0.9276 | 0.8568 |
| 0.0011 | 23.0100 | 14928 | 1.0031 | 0.8568 |
| 0.0002 | 24.0100 | 15550 | 0.9453 | 0.8568 |