metadata
library_name: transformers
base_model: google/mobilenet_v2_1.0_224
tags:
- image-classification
- vision
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mobilenetv2-typecoffee
results: []
mobilenetv2-typecoffee
This model is a fine-tuned version of google/mobilenet_v2_1.0_224 on the Master-Rapha7/TypeCoffee_128x128 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3891
- Accuracy: 0.8705
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: 16
- eval_batch_size: 16
- seed: 42
- 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: 50.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.0566 | 1.0 | 364 | 1.3442 | 0.4711 |
| 0.7958 | 2.0 | 728 | 0.9054 | 0.6309 |
| 0.7631 | 3.0 | 1092 | 1.8326 | 0.3444 |
| 0.8108 | 4.0 | 1456 | 1.5297 | 0.5 |
| 0.9185 | 5.0 | 1820 | 2.1793 | 0.4366 |
| 0.5972 | 6.0 | 2184 | 0.7575 | 0.7383 |
| 0.5495 | 7.0 | 2548 | 1.5874 | 0.6006 |
| 0.5987 | 8.0 | 2912 | 1.1093 | 0.6680 |
| 0.4262 | 9.0 | 3276 | 0.9131 | 0.6915 |
| 0.5068 | 10.0 | 3640 | 2.0110 | 0.5937 |
| 0.4457 | 11.0 | 4004 | 0.8147 | 0.7603 |
| 0.4789 | 12.0 | 4368 | 0.4532 | 0.8512 |
| 0.5156 | 13.0 | 4732 | 0.6730 | 0.8058 |
| 0.3494 | 14.0 | 5096 | 1.2551 | 0.6584 |
| 0.5386 | 15.0 | 5460 | 1.2512 | 0.6171 |
| 0.3413 | 16.0 | 5824 | 0.8357 | 0.7383 |
| 0.4416 | 17.0 | 6188 | 1.2328 | 0.6791 |
| 0.3827 | 18.0 | 6552 | 0.6589 | 0.8044 |
| 0.3838 | 19.0 | 6916 | 1.0300 | 0.6983 |
| 0.4336 | 20.0 | 7280 | 1.1139 | 0.7011 |
| 0.3418 | 21.0 | 7644 | 0.6383 | 0.7948 |
| 0.4024 | 22.0 | 8008 | 3.2976 | 0.4421 |
| 0.4106 | 23.0 | 8372 | 0.7275 | 0.7796 |
| 0.3289 | 24.0 | 8736 | 2.0388 | 0.6088 |
| 0.5709 | 25.0 | 9100 | 2.2146 | 0.6391 |
| 0.2912 | 26.0 | 9464 | 0.9518 | 0.7410 |
| 0.433 | 27.0 | 9828 | 1.8215 | 0.6901 |
| 0.2391 | 28.0 | 10192 | 0.8574 | 0.7782 |
| 0.2589 | 29.0 | 10556 | 0.7175 | 0.7824 |
| 0.2877 | 30.0 | 10920 | 1.1670 | 0.7273 |
| 0.2391 | 31.0 | 11284 | 0.7039 | 0.7796 |
| 0.3905 | 32.0 | 11648 | 1.0528 | 0.6928 |
| 0.3362 | 33.0 | 12012 | 1.4142 | 0.7218 |
| 0.4056 | 34.0 | 12376 | 0.5757 | 0.8623 |
| 0.2026 | 35.0 | 12740 | 0.8064 | 0.7769 |
| 0.2183 | 36.0 | 13104 | 1.9640 | 0.5964 |
| 0.2996 | 37.0 | 13468 | 1.1046 | 0.7011 |
| 0.1853 | 38.0 | 13832 | 1.2391 | 0.7369 |
| 0.2278 | 39.0 | 14196 | 0.3891 | 0.8705 |
| 0.2415 | 40.0 | 14560 | 0.4691 | 0.8251 |
| 0.2394 | 41.0 | 14924 | 1.4963 | 0.6736 |
| 0.3786 | 42.0 | 15288 | 1.8459 | 0.6804 |
| 0.2873 | 43.0 | 15652 | 2.0178 | 0.5634 |
| 0.2306 | 44.0 | 16016 | 0.7742 | 0.7603 |
| 0.3525 | 45.0 | 16380 | 0.6618 | 0.8140 |
| 0.1891 | 46.0 | 16744 | 1.1009 | 0.7121 |
| 0.2664 | 47.0 | 17108 | 0.8616 | 0.7562 |
| 0.2374 | 48.0 | 17472 | 2.2997 | 0.4766 |
| 0.2761 | 49.0 | 17836 | 1.3257 | 0.7452 |
| 0.2137 | 50.0 | 18200 | 1.0285 | 0.7507 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0