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--- |
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license: cc-by-nc-4.0 |
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base_model: MCG-NJU/videomae-large-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-large |
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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-large |
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This model is a fine-tuned version of [MCG-NJU/videomae-large-finetuned-kinetics](https://huggingface.co/MCG-NJU/videomae-large-finetuned-kinetics) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.5042 |
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- Accuracy: 0.4286 |
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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: 16 |
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- eval_batch_size: 16 |
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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: 220 |
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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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| 2.6619 | 0.03 | 7 | 2.7017 | 0.0 | |
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| 2.6232 | 1.03 | 14 | 2.6628 | 0.0 | |
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| 2.381 | 2.03 | 21 | 2.5798 | 0.1667 | |
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| 2.2215 | 3.03 | 28 | 2.4757 | 0.1667 | |
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| 1.7389 | 4.03 | 35 | 2.3636 | 0.2333 | |
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| 1.3366 | 5.03 | 42 | 2.2424 | 0.3 | |
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| 1.1946 | 6.03 | 49 | 2.1675 | 0.3 | |
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| 0.6809 | 7.03 | 56 | 2.0548 | 0.3667 | |
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| 0.5255 | 8.03 | 63 | 2.0410 | 0.4 | |
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| 0.3285 | 9.03 | 70 | 1.9539 | 0.4 | |
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| 0.2849 | 10.03 | 77 | 1.8536 | 0.4667 | |
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| 0.1832 | 11.03 | 84 | 1.8293 | 0.4333 | |
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| 0.1307 | 12.03 | 91 | 1.8200 | 0.4 | |
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| 0.0901 | 13.03 | 98 | 1.8355 | 0.4 | |
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| 0.0636 | 14.03 | 105 | 1.8201 | 0.4333 | |
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| 0.0413 | 15.03 | 112 | 1.7750 | 0.4667 | |
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| 0.0427 | 16.03 | 119 | 1.7460 | 0.5333 | |
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| 0.0254 | 17.03 | 126 | 1.7804 | 0.5333 | |
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| 0.0203 | 18.03 | 133 | 1.8869 | 0.4333 | |
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| 0.0174 | 19.03 | 140 | 1.7741 | 0.5667 | |
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| 0.0154 | 20.03 | 147 | 1.7401 | 0.5333 | |
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| 0.0136 | 21.03 | 154 | 1.7672 | 0.5 | |
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| 0.0116 | 22.03 | 161 | 1.7793 | 0.5333 | |
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| 0.0123 | 23.03 | 168 | 1.8018 | 0.4667 | |
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| 0.0102 | 24.03 | 175 | 1.8024 | 0.5 | |
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| 0.0103 | 25.03 | 182 | 1.8058 | 0.5 | |
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| 0.0089 | 26.03 | 189 | 1.8106 | 0.5 | |
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| 0.0088 | 27.03 | 196 | 1.8029 | 0.5 | |
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| 0.0092 | 28.03 | 203 | 1.7961 | 0.5 | |
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| 0.0083 | 29.03 | 210 | 1.7940 | 0.5 | |
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| 0.0099 | 30.03 | 217 | 1.7922 | 0.5 | |
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| 0.0085 | 31.01 | 220 | 1.7920 | 0.5 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.17.1 |
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- Tokenizers 0.15.2 |
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