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# mobilenet_v1_0.75_192-finetuned-ind-5-balanced-1000

This model is a fine-tuned version of [google/mobilenet_v1_0.75_192](https://huggingface.co/google/mobilenet_v1_0.75_192) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0114
- Accuracy: 0.7363
- Recall: 0.7363
- F1: 0.7251
- Precision: 0.7258

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
| 1.5992        | 0.97  | 22   | 1.5748          | 0.5275   | 0.5275 | 0.4724 | 0.5585    |
| 1.5129        | 1.98  | 45   | 1.4053          | 0.4890   | 0.4890 | 0.4063 | 0.4136    |
| 1.3803        | 2.99  | 68   | 1.2587          | 0.5659   | 0.5659 | 0.5270 | 0.5609    |
| 1.2055        | 4.0   | 91   | 1.1328          | 0.5330   | 0.5330 | 0.4917 | 0.5783    |
| 1.1293        | 4.97  | 113  | 1.0423          | 0.7198   | 0.7198 | 0.7120 | 0.7194    |
| 1.117         | 5.98  | 136  | 1.0064          | 0.6154   | 0.6154 | 0.5702 | 0.6331    |
| 1.0456        | 6.99  | 159  | 0.9141          | 0.7143   | 0.7143 | 0.7156 | 0.7194    |
| 1.0187        | 8.0   | 182  | 1.0695          | 0.5165   | 0.5165 | 0.4969 | 0.5738    |
| 1.0067        | 8.97  | 204  | 0.8928          | 0.7088   | 0.7088 | 0.7033 | 0.7111    |
| 0.9848        | 9.67  | 220  | 0.9363          | 0.6648   | 0.6648 | 0.6477 | 0.6602    |


### 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_v1_0.75_192", "model-index": [{"name": "mobilenet_v1_0.75_192-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": 0.7362637362637363, "name": "Accuracy"}, {"type": "recall", "value": 0.7362637362637363, "name": "Recall"}, {"type": "f1", "value": 0.7251076414098591, "name": "F1"}, {"type": "precision", "value": 0.7257522400379544, "name": "Precision"}]}]}]}
transformers tensorboard safetensors mobilenet_v1 image-classification generated_from_trainer dataset:imagefolder base_model:google/mobilenet_v1_0.75_192 license:other model-index autotrain_compatible endpoints_compatible region:us