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# resnet-101-finetuned-ind-5-balanced-1000

This model is a fine-tuned version of [microsoft/resnet-101](https://huggingface.co/microsoft/resnet-101) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 6306179.0
- Accuracy: 0.2088
- Recall: 0.2088
- F1: 0.1324
- Precision: 0.2821

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
| 324878105.6   | 0.97  | 22   | 15181631.0      | 0.1703   | 0.1703 | 0.0755 | 0.0759    |
| 218756556.8   | 1.98  | 45   | 36161572.0      | 0.2033   | 0.2033 | 0.1015 | 0.2224    |
| 139746355.2   | 2.99  | 68   | 17319910.0      | 0.2033   | 0.2033 | 0.1090 | 0.1978    |
| 51751814.4    | 4.0   | 91   | 11496959.0      | 0.2033   | 0.2033 | 0.1008 | 0.1504    |
| 35621248.0    | 4.97  | 113  | 9639349.0       | 0.2143   | 0.2143 | 0.1382 | 0.2099    |
| 51569808.0    | 5.98  | 136  | 7263810.0       | 0.2033   | 0.2033 | 0.1162 | 0.2052    |
| 58063296.0    | 6.99  | 159  | 5746364.0       | 0.2363   | 0.2363 | 0.1787 | 0.3630    |
| 24195684.8    | 8.0   | 182  | 9682259.0       | 0.1868   | 0.1868 | 0.0962 | 0.1119    |
| 17002955.2    | 8.97  | 204  | 17657684.0      | 0.2527   | 0.2527 | 0.1795 | 0.3426    |
| 20084712.0    | 9.67  | 220  | 10674498.0      | 0.2253   | 0.2253 | 0.1479 | 0.2321    |


### Framework versions

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

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy", "recall", "f1", "precision"], "base_model": "microsoft/resnet-101", "model-index": [{"name": "resnet-101-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": 0.1323833823833824, "name": "F1"}, {"type": "precision", "value": 0.28205128205128205, "name": "Precision"}]}]}]}
transformers tensorboard safetensors resnet image-classification generated_from_trainer dataset:imagefolder base_model:microsoft/resnet-101 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us