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# mobilenet_v2_1.0_224-finetuned-ind-5-balanced-1000

This model is a fine-tuned version of [google/mobilenet_v2_1.0_224](https://huggingface.co/google/mobilenet_v2_1.0_224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 8773717432279338104756995316776960.0000
- Accuracy: 0.2088
- Recall: 0.2088
- F1: 0.0969
- Precision: 0.0939

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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 | Recall | F1     | Precision |
|:----------------------------------------:|:-----:|:----:|:---------------------------------------:|:--------:|:------:|:------:|:---------:|
| 8502058299328377473021894451003392.0000  | 0.97  | 22   | 5544083517438593426628855359078400.0000 | 0.1978   | 0.1978 | 0.0656 | 0.0393    |
| 11001842504881722540607733185380352.0000 | 1.98  | 45   | 8960026170251748550749038613364736.0000 | 0.1923   | 0.1923 | 0.0644 | 0.0387    |
| 11144414573678173566748739128786944.0000 | 2.99  | 68   | 4530373723864042830337690579238912.0000 | 0.2033   | 0.2033 | 0.0763 | 0.0984    |
| 8727814987004647759193517338918912.0000  | 4.0   | 91   | 4781932114912116921204185640206336.0000 | 0.1703   | 0.1703 | 0.0584 | 0.0352    |
| 9518708138599229113781231827288064.0000  | 4.97  | 113  | 4184824425848216420754410786783232.0000 | 0.1868   | 0.1868 | 0.0631 | 0.0380    |
| 8719844633855713458584509581623296.0000  | 5.98  | 136  | 5665474060780858888315051131797504.0000 | 0.2253   | 0.2253 | 0.1137 | 0.1166    |
| 8380181616932684411917444870832128.0000  | 6.99  | 159  | 6091166358999981531515025327390720.0000 | 0.1978   | 0.1978 | 0.0672 | 0.0405    |
| 8983794247624016296997320250097664.0000  | 8.0   | 182  | 5735566844775216762169976994922496.0000 | 0.1923   | 0.1923 | 0.0656 | 0.0396    |
| 8958987909940799671728179796508672.0000  | 8.97  | 204  | 6867187022756591794849527384506368.0000 | 0.2088   | 0.2088 | 0.0855 | 0.0909    |
| 7603907051674017178257162846076928.0000  | 9.67  | 220  | 8926725583194971821354252171739136.0000 | 0.2033   | 0.2033 | 0.0764 | 0.0698    |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0

{"license": "other", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy", "recall", "f1", "precision"], "base_model": "google/mobilenet_v2_1.0_224", "model-index": [{"name": "mobilenet_v2_1.0_224-finetuned-ind-5-balanced-1000", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "train", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.2087912087912088, "name": "Accuracy"}, {"type": "recall", "value": 0.2087912087912088, "name": "Recall"}, {"type": "f1", "value": 0.09687006760177494, "name": "F1"}, {"type": "precision", "value": 0.09389427140906431, "name": "Precision"}]}]}]}
transformers tensorboard safetensors mobilenet_v2 image-classification generated_from_trainer dataset:imagefolder base_model:google/mobilenet_v2_1.0_224 license:other model-index autotrain_compatible endpoints_compatible region:us