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# resnet-152-finetuned_resnet152-adam-optimizere-2-autotags

This model is a fine-tuned version of [microsoft/resnet-152](https://huggingface.co/microsoft/resnet-152) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4368
- Accuracy: 0.8981

## 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: 0.01
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4424        | 0.99  | 65   | 1.7123          | 0.56     |
| 1.6053        | 1.99  | 130  | 2.0613          | 0.3152   |
| 1.3795        | 2.99  | 195  | 1.3791          | 0.5552   |
| 0.9701        | 3.99  | 260  | 0.9195          | 0.7038   |
| 0.8258        | 4.99  | 325  | 0.9107          | 0.7067   |
| 0.7619        | 5.99  | 390  | 0.9915          | 0.6867   |
| 0.6241        | 6.99  | 455  | 0.7895          | 0.76     |
| 0.497         | 7.99  | 520  | 0.6616          | 0.8038   |
| 0.4709        | 8.99  | 585  | 0.5282          | 0.8543   |
| 0.394         | 9.99  | 650  | 0.5447          | 0.8429   |
| 0.343         | 10.99 | 715  | 0.5108          | 0.8486   |
| 0.3482        | 11.99 | 780  | 0.5224          | 0.8505   |
| 0.2576        | 12.99 | 845  | 0.4796          | 0.8743   |
| 0.1837        | 13.99 | 910  | 0.5008          | 0.8571   |
| 0.1904        | 14.99 | 975  | 0.4366          | 0.8790   |
| 0.1458        | 15.99 | 1040 | 0.4320          | 0.8990   |
| 0.1575        | 16.99 | 1105 | 0.4059          | 0.8952   |
| 0.0992        | 17.99 | 1170 | 0.4362          | 0.8952   |
| 0.0858        | 18.99 | 1235 | 0.4210          | 0.8971   |
| 0.0704        | 19.99 | 1300 | 0.4368          | 0.8981   |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.1+cu117
- Datasets 2.11.0
- Tokenizers 0.13.2

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