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---
license: other
base_model: google/mobilenet_v2_1.0_224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mobilenet_v2-activity-recognition
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# mobilenet_v2-activity-recognition
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.
It achieves the following results on the evaluation set:
- Loss: 1.0450
- Accuracy: 0.6718
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 2.8136 | 0.1778 | 10 | 2.7919 | 0.0733 |
| 2.8041 | 0.3556 | 20 | 2.7240 | 0.1043 |
| 2.6841 | 0.5333 | 30 | 2.6304 | 0.1421 |
| 2.5799 | 0.7111 | 40 | 2.4856 | 0.2497 |
| 2.4537 | 0.8889 | 50 | 2.3143 | 0.3431 |
| 2.2593 | 1.0667 | 60 | 2.1425 | 0.4005 |
| 2.0671 | 1.2444 | 70 | 1.9995 | 0.4360 |
| 1.8958 | 1.4222 | 80 | 1.8545 | 0.4683 |
| 1.7891 | 1.6 | 90 | 1.7437 | 0.4939 |
| 1.6659 | 1.7778 | 100 | 1.6373 | 0.5317 |
| 1.6006 | 1.9556 | 110 | 1.5372 | 0.5568 |
| 1.4752 | 2.1333 | 120 | 1.4766 | 0.5705 |
| 1.3654 | 2.3111 | 130 | 1.4303 | 0.5862 |
| 1.3452 | 2.4889 | 140 | 1.3513 | 0.6048 |
| 1.3134 | 2.6667 | 150 | 1.3941 | 0.5663 |
| 1.2905 | 2.8444 | 160 | 1.2859 | 0.6159 |
| 1.2201 | 3.0222 | 170 | 1.2661 | 0.6174 |
| 1.1225 | 3.2 | 180 | 1.2662 | 0.6181 |
| 1.0991 | 3.3778 | 190 | 1.1911 | 0.6392 |
| 1.1171 | 3.5556 | 200 | 1.2437 | 0.6142 |
| 1.0643 | 3.7333 | 210 | 1.1952 | 0.6318 |
| 1.1095 | 3.9111 | 220 | 1.1333 | 0.6519 |
| 1.0284 | 4.0889 | 230 | 1.1642 | 0.6362 |
| 0.9896 | 4.2667 | 240 | 1.1140 | 0.6519 |
| 0.9507 | 4.4444 | 250 | 1.0811 | 0.6672 |
| 0.9437 | 4.6222 | 260 | 1.0729 | 0.6652 |
| 0.9522 | 4.8 | 270 | 1.0724 | 0.6650 |
| 0.953 | 4.9778 | 280 | 1.0645 | 0.6713 |
| 0.8857 | 5.1556 | 290 | 1.1049 | 0.6508 |
| 0.907 | 5.3333 | 300 | 1.0808 | 0.6580 |
| 0.8723 | 5.5111 | 310 | 1.0437 | 0.6766 |
| 0.824 | 5.6889 | 320 | 1.0227 | 0.6801 |
| 0.846 | 5.8667 | 330 | 1.0186 | 0.6746 |
| 0.845 | 6.0444 | 340 | 1.0166 | 0.6805 |
| 0.8015 | 6.2222 | 350 | 1.0379 | 0.6720 |
| 0.8798 | 6.4 | 360 | 0.9889 | 0.6879 |
| 0.8076 | 6.5778 | 370 | 1.0059 | 0.6829 |
| 0.8105 | 6.7556 | 380 | 1.0098 | 0.6783 |
| 0.7414 | 6.9333 | 390 | 0.9801 | 0.6859 |
| 0.7869 | 7.1111 | 400 | 0.9624 | 0.6993 |
| 0.7728 | 7.2889 | 410 | 1.0938 | 0.6547 |
| 0.7762 | 7.4667 | 420 | 0.9867 | 0.6825 |
| 0.7769 | 7.6444 | 430 | 1.0512 | 0.6670 |
| 0.7563 | 7.8222 | 440 | 1.0346 | 0.6770 |
| 0.762 | 8.0 | 450 | 1.0647 | 0.6597 |
| 0.726 | 8.1778 | 460 | 1.0134 | 0.6812 |
| 0.7515 | 8.3556 | 470 | 0.9921 | 0.6787 |
| 0.7034 | 8.5333 | 480 | 1.0043 | 0.6833 |
| 0.7426 | 8.7111 | 490 | 0.9721 | 0.6936 |
| 0.7225 | 8.8889 | 500 | 1.0450 | 0.6718 |
| 0.7372 | 9.0667 | 510 | 0.9957 | 0.6812 |
| 0.7238 | 9.2444 | 520 | 0.9928 | 0.6894 |
| 0.7824 | 9.4222 | 530 | 1.0413 | 0.6753 |
| 0.7218 | 9.6 | 540 | 0.9717 | 0.6877 |
| 0.6976 | 9.7778 | 550 | 0.9839 | 0.6859 |
| 0.7288 | 9.9556 | 560 | 1.0229 | 0.6728 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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