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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-soccer-action-recognitionx |
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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-soccer-action-recognitionx |
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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: 0.2575 |
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- Accuracy: 0.9281 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 32 |
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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: 1376 |
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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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| No log | 0.03 | 43 | 1.8151 | 0.3661 | |
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| 1.7589 | 1.03 | 86 | 0.9133 | 0.6915 | |
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| 1.7589 | 2.03 | 129 | 0.5026 | 0.7966 | |
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| 0.5494 | 3.03 | 172 | 0.3937 | 0.8678 | |
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| 0.5494 | 4.03 | 215 | 0.3943 | 0.8678 | |
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| 0.2747 | 5.03 | 258 | 0.3876 | 0.8678 | |
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| 0.2747 | 6.03 | 301 | 0.2803 | 0.9085 | |
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| 0.1731 | 7.03 | 345 | 0.2414 | 0.9119 | |
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| 0.1731 | 8.03 | 388 | 0.2434 | 0.9288 | |
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| 0.1165 | 9.03 | 431 | 0.1560 | 0.9458 | |
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| 0.1165 | 10.03 | 474 | 0.1894 | 0.9254 | |
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| 0.07 | 11.03 | 517 | 0.2401 | 0.9153 | |
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| 0.0417 | 12.03 | 560 | 0.1883 | 0.9390 | |
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| 0.0417 | 13.03 | 603 | 0.2589 | 0.9051 | |
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| 0.0362 | 14.03 | 646 | 0.2125 | 0.9492 | |
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| 0.0362 | 15.03 | 690 | 0.2228 | 0.9390 | |
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| 0.0348 | 16.03 | 733 | 0.1797 | 0.9525 | |
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| 0.0348 | 17.03 | 776 | 0.1728 | 0.9390 | |
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| 0.0129 | 18.03 | 819 | 0.2253 | 0.9254 | |
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| 0.0129 | 19.03 | 862 | 0.1983 | 0.9356 | |
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| 0.0112 | 20.03 | 905 | 0.2821 | 0.9220 | |
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| 0.0112 | 21.03 | 948 | 0.2527 | 0.9356 | |
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| 0.0165 | 22.03 | 991 | 0.2598 | 0.9288 | |
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| 0.0165 | 23.03 | 1035 | 0.2690 | 0.9288 | |
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| 0.0056 | 24.03 | 1078 | 0.2817 | 0.9220 | |
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| 0.0026 | 25.03 | 1121 | 0.2039 | 0.9424 | |
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| 0.0026 | 26.03 | 1164 | 0.2164 | 0.9458 | |
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| 0.0033 | 27.03 | 1207 | 0.2063 | 0.9424 | |
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| 0.0033 | 28.03 | 1250 | 0.1836 | 0.9525 | |
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| 0.0038 | 29.03 | 1293 | 0.1899 | 0.9458 | |
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| 0.0038 | 30.03 | 1336 | 0.1815 | 0.9492 | |
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| 0.0024 | 31.03 | 1376 | 0.1816 | 0.9525 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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