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--- |
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license: cc-by-nc-4.0 |
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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-engine-subset-20230310 |
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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-engine-subset-20230310 |
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This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-NJU/videomae-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4958 |
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- Accuracy: 0.85 |
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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: 5e-05 |
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- train_batch_size: 6 |
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- eval_batch_size: 6 |
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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: 600 |
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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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| 2.5947 | 0.05 | 31 | 2.5383 | 0.15 | |
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| 2.4195 | 1.05 | 62 | 2.5108 | 0.15 | |
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| 2.2476 | 2.05 | 93 | 2.0533 | 0.225 | |
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| 1.9449 | 3.05 | 124 | 2.0719 | 0.2375 | |
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| 1.5724 | 4.05 | 155 | 1.4756 | 0.475 | |
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| 1.395 | 5.05 | 186 | 1.2884 | 0.5 | |
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| 1.0822 | 6.05 | 217 | 1.0679 | 0.575 | |
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| 1.0635 | 7.05 | 248 | 0.8040 | 0.7 | |
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| 0.8707 | 8.05 | 279 | 0.9334 | 0.525 | |
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| 0.7042 | 9.05 | 310 | 0.6477 | 0.75 | |
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| 0.6543 | 10.05 | 341 | 0.6963 | 0.7375 | |
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| 0.6807 | 11.05 | 372 | 0.4958 | 0.85 | |
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| 0.4924 | 12.05 | 403 | 0.6374 | 0.775 | |
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| 0.4822 | 13.05 | 434 | 0.6145 | 0.75 | |
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| 0.4878 | 14.05 | 465 | 0.6274 | 0.7625 | |
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| 0.4442 | 15.05 | 496 | 0.4231 | 0.85 | |
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| 0.2739 | 16.05 | 527 | 0.4999 | 0.85 | |
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| 0.3514 | 17.05 | 558 | 0.4639 | 0.8375 | |
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| 0.4158 | 18.05 | 589 | 0.4291 | 0.85 | |
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| 0.2689 | 19.02 | 600 | 0.4294 | 0.85 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.10.1 |
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- Tokenizers 0.13.2 |
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