
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# resnet-50_finetuned

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: 0.7209
- Precision: 0.3702
- Recall: 0.5
- F1: 0.4254
- Accuracy: 0.7404

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 46   | 0.6599          | 0.3702    | 0.5    | 0.4254 | 0.7404   |
| No log        | 2.0   | 92   | 0.6725          | 0.3702    | 0.5    | 0.4254 | 0.7404   |
| No log        | 3.0   | 138  | nan             | 0.8714    | 0.5062 | 0.4384 | 0.7436   |
| No log        | 4.0   | 184  | nan             | 0.8714    | 0.5062 | 0.4384 | 0.7436   |
| No log        | 5.0   | 230  | nan             | 0.8714    | 0.5062 | 0.4384 | 0.7436   |
| No log        | 6.0   | 276  | nan             | 0.8714    | 0.5062 | 0.4384 | 0.7436   |
| No log        | 7.0   | 322  | nan             | 0.8714    | 0.5062 | 0.4384 | 0.7436   |
| No log        | 8.0   | 368  | nan             | 0.8714    | 0.5062 | 0.4384 | 0.7436   |
| No log        | 9.0   | 414  | nan             | 0.8714    | 0.5062 | 0.4384 | 0.7436   |
| No log        | 10.0  | 460  | 0.7209          | 0.3702    | 0.5    | 0.4254 | 0.7404   |


### Framework versions

- Transformers 4.22.1
- Pytorch 1.12.1+cu113
- Datasets 2.5.1
- Tokenizers 0.12.1

illustrated not-illustrated