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--- |
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license: other |
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base_model: google/mobilenet_v2_1.0_224 |
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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: mobilenet_v2-activity-recognition |
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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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# mobilenet_v2-activity-recognition |
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This model is a fine-tuned version of [google/mobilenet_v2_1.0_224](https://huggingface.co/google/mobilenet_v2_1.0_224) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0450 |
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- Accuracy: 0.6718 |
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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: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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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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- num_epochs: 10 |
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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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| 2.8136 | 0.1778 | 10 | 2.7919 | 0.0733 | |
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| 2.8041 | 0.3556 | 20 | 2.7240 | 0.1043 | |
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| 2.6841 | 0.5333 | 30 | 2.6304 | 0.1421 | |
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| 2.5799 | 0.7111 | 40 | 2.4856 | 0.2497 | |
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| 2.4537 | 0.8889 | 50 | 2.3143 | 0.3431 | |
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| 2.2593 | 1.0667 | 60 | 2.1425 | 0.4005 | |
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| 2.0671 | 1.2444 | 70 | 1.9995 | 0.4360 | |
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| 1.8958 | 1.4222 | 80 | 1.8545 | 0.4683 | |
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| 1.7891 | 1.6 | 90 | 1.7437 | 0.4939 | |
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| 1.6659 | 1.7778 | 100 | 1.6373 | 0.5317 | |
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| 1.6006 | 1.9556 | 110 | 1.5372 | 0.5568 | |
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| 1.4752 | 2.1333 | 120 | 1.4766 | 0.5705 | |
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| 1.3654 | 2.3111 | 130 | 1.4303 | 0.5862 | |
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| 1.3452 | 2.4889 | 140 | 1.3513 | 0.6048 | |
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| 1.3134 | 2.6667 | 150 | 1.3941 | 0.5663 | |
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| 1.2905 | 2.8444 | 160 | 1.2859 | 0.6159 | |
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| 1.2201 | 3.0222 | 170 | 1.2661 | 0.6174 | |
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| 1.1225 | 3.2 | 180 | 1.2662 | 0.6181 | |
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| 1.0991 | 3.3778 | 190 | 1.1911 | 0.6392 | |
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| 1.1171 | 3.5556 | 200 | 1.2437 | 0.6142 | |
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| 1.0643 | 3.7333 | 210 | 1.1952 | 0.6318 | |
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| 1.1095 | 3.9111 | 220 | 1.1333 | 0.6519 | |
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| 1.0284 | 4.0889 | 230 | 1.1642 | 0.6362 | |
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| 0.9896 | 4.2667 | 240 | 1.1140 | 0.6519 | |
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| 0.9507 | 4.4444 | 250 | 1.0811 | 0.6672 | |
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| 0.9437 | 4.6222 | 260 | 1.0729 | 0.6652 | |
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| 0.9522 | 4.8 | 270 | 1.0724 | 0.6650 | |
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| 0.953 | 4.9778 | 280 | 1.0645 | 0.6713 | |
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| 0.8857 | 5.1556 | 290 | 1.1049 | 0.6508 | |
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| 0.907 | 5.3333 | 300 | 1.0808 | 0.6580 | |
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| 0.8723 | 5.5111 | 310 | 1.0437 | 0.6766 | |
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| 0.824 | 5.6889 | 320 | 1.0227 | 0.6801 | |
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| 0.846 | 5.8667 | 330 | 1.0186 | 0.6746 | |
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| 0.845 | 6.0444 | 340 | 1.0166 | 0.6805 | |
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| 0.8015 | 6.2222 | 350 | 1.0379 | 0.6720 | |
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| 0.8798 | 6.4 | 360 | 0.9889 | 0.6879 | |
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| 0.8076 | 6.5778 | 370 | 1.0059 | 0.6829 | |
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| 0.8105 | 6.7556 | 380 | 1.0098 | 0.6783 | |
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| 0.7414 | 6.9333 | 390 | 0.9801 | 0.6859 | |
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| 0.7869 | 7.1111 | 400 | 0.9624 | 0.6993 | |
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| 0.7728 | 7.2889 | 410 | 1.0938 | 0.6547 | |
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| 0.7762 | 7.4667 | 420 | 0.9867 | 0.6825 | |
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| 0.7769 | 7.6444 | 430 | 1.0512 | 0.6670 | |
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| 0.7563 | 7.8222 | 440 | 1.0346 | 0.6770 | |
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| 0.762 | 8.0 | 450 | 1.0647 | 0.6597 | |
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| 0.726 | 8.1778 | 460 | 1.0134 | 0.6812 | |
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| 0.7515 | 8.3556 | 470 | 0.9921 | 0.6787 | |
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| 0.7034 | 8.5333 | 480 | 1.0043 | 0.6833 | |
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| 0.7426 | 8.7111 | 490 | 0.9721 | 0.6936 | |
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| 0.7225 | 8.8889 | 500 | 1.0450 | 0.6718 | |
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| 0.7372 | 9.0667 | 510 | 0.9957 | 0.6812 | |
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| 0.7238 | 9.2444 | 520 | 0.9928 | 0.6894 | |
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| 0.7824 | 9.4222 | 530 | 1.0413 | 0.6753 | |
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| 0.7218 | 9.6 | 540 | 0.9717 | 0.6877 | |
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| 0.6976 | 9.7778 | 550 | 0.9839 | 0.6859 | |
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| 0.7288 | 9.9556 | 560 | 1.0229 | 0.6728 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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