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# resnet50_rvl-cdip

This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8368
- Accuracy: 0.7503
- Brier Loss: 0.3458
- Nll: 3.2289
- F1 Micro: 0.7503
- F1 Macro: 0.5224
- Ece: 0.0166
- Aurc: 0.0739

## 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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 1024
- 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 | Brier Loss | Nll    | F1 Micro | F1 Macro | Ece    | Aurc   |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:----------:|:------:|:--------:|:--------:|:------:|:------:|
| No log        | 1.0   | 312  | 3.9686          | 0.1994   | 0.9069     | 6.9377 | 0.1994   | 0.0036   | 0.0434 | 0.6332 |
| 5.3078        | 2.0   | 625  | 1.5040          | 0.5644   | 0.5696     | 4.9767 | 0.5644   | 0.0480   | 0.0330 | 0.2052 |
| 5.3078        | 3.0   | 937  | 1.1500          | 0.6602   | 0.4588     | 4.0574 | 0.6602   | 0.1527   | 0.0193 | 0.1309 |
| 1.3983        | 4.0   | 1250 | 1.0174          | 0.6961   | 0.4132     | 3.6856 | 0.6961   | 0.2658   | 0.0184 | 0.1053 |
| 1.0466        | 5.0   | 1562 | 0.9439          | 0.7167   | 0.3862     | 3.5182 | 0.7167   | 0.3477   | 0.0150 | 0.0921 |
| 1.0466        | 6.0   | 1875 | 0.9042          | 0.7302   | 0.3717     | 3.3972 | 0.7302   | 0.3345   | 0.0160 | 0.0854 |
| 0.9333        | 7.0   | 2187 | 0.8713          | 0.7395   | 0.3593     | 3.3567 | 0.7395   | 0.4236   | 0.0162 | 0.0801 |
| 0.8757        | 8.0   | 2500 | 0.8550          | 0.7444   | 0.3531     | 3.2398 | 0.7444   | 0.4113   | 0.0150 | 0.0772 |
| 0.8757        | 9.0   | 2812 | 0.8389          | 0.7487   | 0.3468     | 3.1800 | 0.7487   | 0.4613   | 0.0149 | 0.0745 |
| 0.8509        | 9.98  | 3120 | 0.8368          | 0.7503   | 0.3458     | 3.2289 | 0.7503   | 0.5224   | 0.0166 | 0.0739 |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.2.0.dev20231112+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "microsoft/resnet-50", "model-index": [{"name": "resnet50_rvl-cdip", "results": []}]}
transformers safetensors resnet image-classification generated_from_trainer base_model:microsoft/resnet-50 license:apache-2.0 autotrain_compatible endpoints_compatible region:us