|
--- |
|
library_name: transformers |
|
license: other |
|
base_model: google/mobilenet_v2_1.0_224 |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: mobilenetv2-cocoa |
|
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. --> |
|
|
|
# mobilenetv2-cocoa |
|
|
|
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: 0.6160 |
|
- Accuracy: 0.8881 |
|
|
|
## 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: 2e-05 |
|
- train_batch_size: 8 |
|
- eval_batch_size: 8 |
|
- seed: 1337 |
|
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
|
- lr_scheduler_type: linear |
|
- num_epochs: 100.0 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
|
| 0.569 | 1.0 | 196 | 0.5072 | 0.8628 | |
|
| 0.3973 | 2.0 | 392 | 0.4278 | 0.8700 | |
|
| 0.5873 | 3.0 | 588 | 0.4138 | 0.8773 | |
|
| 0.4781 | 4.0 | 784 | 0.4718 | 0.8736 | |
|
| 0.4483 | 5.0 | 980 | 0.4506 | 0.8773 | |
|
| 0.655 | 6.0 | 1176 | 0.3685 | 0.8953 | |
|
| 0.3441 | 7.0 | 1372 | 0.4751 | 0.8773 | |
|
| 0.3166 | 8.0 | 1568 | 0.3796 | 0.8809 | |
|
| 0.5114 | 9.0 | 1764 | 0.4087 | 0.8917 | |
|
| 0.6452 | 10.0 | 1960 | 0.3760 | 0.8989 | |
|
| 0.4747 | 11.0 | 2156 | 0.4223 | 0.8773 | |
|
| 0.5145 | 12.0 | 2352 | 1.1704 | 0.5957 | |
|
| 0.1991 | 13.0 | 2548 | 0.3454 | 0.9097 | |
|
| 0.2396 | 14.0 | 2744 | 0.3913 | 0.8700 | |
|
| 0.3259 | 15.0 | 2940 | 0.3689 | 0.8881 | |
|
| 0.3434 | 16.0 | 3136 | 0.3743 | 0.8736 | |
|
| 0.389 | 17.0 | 3332 | 0.3657 | 0.9025 | |
|
| 0.302 | 18.0 | 3528 | 0.4218 | 0.8917 | |
|
| 0.4693 | 19.0 | 3724 | 0.3226 | 0.8953 | |
|
| 0.6346 | 20.0 | 3920 | 0.3277 | 0.8881 | |
|
| 0.481 | 21.0 | 4116 | 0.3484 | 0.8700 | |
|
| 0.2628 | 22.0 | 4312 | 0.3942 | 0.9025 | |
|
| 0.3653 | 23.0 | 4508 | 0.3537 | 0.8989 | |
|
| 0.344 | 24.0 | 4704 | 0.4758 | 0.8809 | |
|
| 0.2819 | 25.0 | 4900 | 0.4318 | 0.8989 | |
|
| 0.513 | 26.0 | 5096 | 0.4277 | 0.8412 | |
|
| 0.201 | 27.0 | 5292 | 0.3915 | 0.8953 | |
|
| 0.2696 | 28.0 | 5488 | 0.4401 | 0.8809 | |
|
| 0.4204 | 29.0 | 5684 | 0.3856 | 0.8953 | |
|
| 0.316 | 30.0 | 5880 | 0.3576 | 0.8845 | |
|
| 0.3102 | 31.0 | 6076 | 0.4155 | 0.8809 | |
|
| 0.1489 | 32.0 | 6272 | 0.4147 | 0.8953 | |
|
| 0.3302 | 33.0 | 6468 | 0.4217 | 0.8953 | |
|
| 0.3271 | 34.0 | 6664 | 0.3321 | 0.9097 | |
|
| 0.3481 | 35.0 | 6860 | 0.3828 | 0.8809 | |
|
| 0.3329 | 36.0 | 7056 | 0.4045 | 0.8700 | |
|
| 0.2471 | 37.0 | 7252 | 0.5536 | 0.8664 | |
|
| 0.2007 | 38.0 | 7448 | 0.3503 | 0.8881 | |
|
| 0.7535 | 39.0 | 7644 | 0.4819 | 0.8809 | |
|
| 0.1851 | 40.0 | 7840 | 0.3762 | 0.8773 | |
|
| 0.2329 | 41.0 | 8036 | 0.4465 | 0.8845 | |
|
| 0.2889 | 42.0 | 8232 | 0.4696 | 0.9061 | |
|
| 0.1409 | 43.0 | 8428 | 0.4876 | 0.8809 | |
|
| 0.2683 | 44.0 | 8624 | 0.6134 | 0.8809 | |
|
| 0.3535 | 45.0 | 8820 | 0.4364 | 0.8809 | |
|
| 0.1683 | 46.0 | 9016 | 0.4059 | 0.8881 | |
|
| 0.43 | 47.0 | 9212 | 0.3955 | 0.8881 | |
|
| 0.5702 | 48.0 | 9408 | 0.3898 | 0.8809 | |
|
| 0.8043 | 49.0 | 9604 | 0.5963 | 0.8953 | |
|
| 0.3742 | 50.0 | 9800 | 0.5273 | 0.8989 | |
|
| 0.1026 | 51.0 | 9996 | 0.3999 | 0.8989 | |
|
| 0.2357 | 52.0 | 10192 | 0.4724 | 0.8592 | |
|
| 0.2612 | 53.0 | 10388 | 0.4169 | 0.8845 | |
|
| 0.4747 | 54.0 | 10584 | 0.3973 | 0.8917 | |
|
| 0.4943 | 55.0 | 10780 | 0.5156 | 0.9061 | |
|
| 0.2296 | 56.0 | 10976 | 0.6397 | 0.8917 | |
|
| 0.1789 | 57.0 | 11172 | 0.5098 | 0.8267 | |
|
| 0.4355 | 58.0 | 11368 | 0.5032 | 0.8917 | |
|
| 0.3957 | 59.0 | 11564 | 0.4205 | 0.9025 | |
|
| 0.4806 | 60.0 | 11760 | 0.7011 | 0.8917 | |
|
| 0.2356 | 61.0 | 11956 | 0.7832 | 0.8881 | |
|
| 0.3865 | 62.0 | 12152 | 0.4622 | 0.8917 | |
|
| 0.3504 | 63.0 | 12348 | 0.5889 | 0.8773 | |
|
| 0.3766 | 64.0 | 12544 | 0.5246 | 0.8592 | |
|
| 0.1336 | 65.0 | 12740 | 0.6462 | 0.8773 | |
|
| 0.3275 | 66.0 | 12936 | 0.5013 | 0.8628 | |
|
| 0.3765 | 67.0 | 13132 | 0.4857 | 0.8953 | |
|
| 0.1622 | 68.0 | 13328 | 0.4918 | 0.8845 | |
|
| 0.2291 | 69.0 | 13524 | 0.5734 | 0.8736 | |
|
| 0.1786 | 70.0 | 13720 | 0.6691 | 0.8231 | |
|
| 0.3451 | 71.0 | 13916 | 0.7318 | 0.8773 | |
|
| 0.2313 | 72.0 | 14112 | 0.5041 | 0.8700 | |
|
| 0.1984 | 73.0 | 14308 | 0.6518 | 0.7690 | |
|
| 0.2345 | 74.0 | 14504 | 0.5280 | 0.8845 | |
|
| 0.0851 | 75.0 | 14700 | 0.6302 | 0.8917 | |
|
| 0.2234 | 76.0 | 14896 | 0.4843 | 0.8809 | |
|
| 0.2266 | 77.0 | 15092 | 0.4900 | 0.8628 | |
|
| 0.2735 | 78.0 | 15288 | 0.5249 | 0.8736 | |
|
| 0.2442 | 79.0 | 15484 | 0.5061 | 0.8917 | |
|
| 0.2246 | 80.0 | 15680 | 0.4810 | 0.8664 | |
|
| 0.3557 | 81.0 | 15876 | 0.6420 | 0.8123 | |
|
| 0.2017 | 82.0 | 16072 | 0.5158 | 0.8845 | |
|
| 0.249 | 83.0 | 16268 | 0.4364 | 0.9025 | |
|
| 0.2566 | 84.0 | 16464 | 0.5507 | 0.8736 | |
|
| 0.1012 | 85.0 | 16660 | 0.4728 | 0.8845 | |
|
| 0.1972 | 86.0 | 16856 | 0.5746 | 0.8809 | |
|
| 0.7922 | 87.0 | 17052 | 0.5262 | 0.8628 | |
|
| 0.1229 | 88.0 | 17248 | 0.6293 | 0.8845 | |
|
| 0.0248 | 89.0 | 17444 | 0.6193 | 0.8881 | |
|
| 0.0925 | 90.0 | 17640 | 0.4755 | 0.8700 | |
|
| 0.1968 | 91.0 | 17836 | 0.5528 | 0.8700 | |
|
| 0.1694 | 92.0 | 18032 | 0.4338 | 0.8953 | |
|
| 0.2083 | 93.0 | 18228 | 1.1286 | 0.8809 | |
|
| 0.3666 | 94.0 | 18424 | 0.6879 | 0.8267 | |
|
| 0.1358 | 95.0 | 18620 | 0.5071 | 0.8881 | |
|
| 0.2247 | 96.0 | 18816 | 0.5941 | 0.8520 | |
|
| 0.2682 | 97.0 | 19012 | 0.5219 | 0.8592 | |
|
| 0.1762 | 98.0 | 19208 | 0.6929 | 0.8520 | |
|
| 0.2368 | 99.0 | 19404 | 0.5324 | 0.8845 | |
|
| 0.1268 | 100.0 | 19600 | 0.6160 | 0.8881 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.48.0.dev0 |
|
- Pytorch 2.5.1+cu124 |
|
- Datasets 3.1.0 |
|
- Tokenizers 0.21.0 |
|
|
