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--- |
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license: cc-by-nc-4.0 |
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base_model: MCG-NJU/videomae-base |
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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-SLT-subset |
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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-SLT-subset |
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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: 1.0411 |
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- Accuracy: 1.0 |
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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: 2 |
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- eval_batch_size: 2 |
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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: 944 |
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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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| 3.9695 | 0.06 | 59 | 3.6889 | 0.05 | |
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| 3.898 | 1.06 | 118 | 3.6205 | 0.05 | |
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| 3.6781 | 2.06 | 177 | 3.4775 | 0.075 | |
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| 3.4169 | 3.06 | 236 | 3.3709 | 0.075 | |
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| 3.6405 | 4.06 | 295 | 3.3190 | 0.075 | |
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| 3.5568 | 5.06 | 354 | 3.3243 | 0.075 | |
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| 3.3347 | 6.06 | 413 | 3.2671 | 0.175 | |
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| 3.3946 | 7.06 | 472 | 3.2436 | 0.15 | |
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| 3.2943 | 8.06 | 531 | 3.2095 | 0.25 | |
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| 3.4037 | 9.06 | 590 | 3.1415 | 0.35 | |
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| 3.3753 | 10.06 | 649 | 2.9745 | 0.7 | |
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| 3.2246 | 11.06 | 708 | 2.5009 | 0.65 | |
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| 2.4989 | 12.06 | 767 | 1.8618 | 0.8 | |
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| 1.905 | 13.06 | 826 | 1.4972 | 0.9 | |
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| 1.7084 | 14.06 | 885 | 1.1309 | 1.0 | |
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| 1.2838 | 15.06 | 944 | 1.0411 | 1.0 | |
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### Framework versions |
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- Transformers 4.34.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.0 |
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