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license: cc-by-nc-4.0 |
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base_model: MCG-NJU/videomae-base-finetuned-kinetics |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: videomae-base-finetuned-kinetics-final-contest-baole4-0705 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# videomae-base-finetuned-kinetics-final-contest-baole4-0705 |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3771 |
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- Accuracy: 0.8807 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- training_steps: 2805 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-------:|:----:|:---------------:|:--------:| |
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| 0.4477 | 0.0670 | 188 | 0.8428 | 0.8486 | |
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| 0.3123 | 1.0670 | 376 | 0.6401 | 0.8532 | |
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| 0.2498 | 2.0670 | 564 | 0.5204 | 0.8578 | |
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| 0.0348 | 3.0670 | 752 | 0.4130 | 0.8899 | |
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| 0.146 | 4.0670 | 940 | 0.3617 | 0.8991 | |
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| 0.038 | 5.0670 | 1128 | 0.4519 | 0.8670 | |
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| 0.0116 | 6.0670 | 1316 | 0.4160 | 0.8716 | |
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| 0.0083 | 7.0670 | 1504 | 0.3683 | 0.8807 | |
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| 0.0067 | 8.0670 | 1692 | 0.3820 | 0.8807 | |
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| 0.0051 | 9.0670 | 1880 | 0.3932 | 0.8761 | |
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| 0.0057 | 10.0670 | 2068 | 0.3944 | 0.8853 | |
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| 0.0045 | 11.0670 | 2256 | 0.4133 | 0.8761 | |
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| 0.0042 | 12.0670 | 2444 | 0.3813 | 0.8807 | |
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| 0.0037 | 13.0670 | 2632 | 0.3806 | 0.8853 | |
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| 0.0039 | 14.0617 | 2805 | 0.3771 | 0.8807 | |
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### Framework versions |
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- Transformers 4.40.2 |
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- Pytorch 1.13.1+cu117 |
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- Datasets 2.18.0 |
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- Tokenizers 0.19.1 |
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