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# organoids-prova_organoid

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3433
- Accuracy: 0.8576

## 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: 1e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2121        | 0.99  | 36   | 1.3066          | 0.4116   |
| 0.8905        | 1.99  | 72   | 0.9344          | 0.6749   |
| 0.6942        | 2.98  | 108  | 0.6875          | 0.7507   |
| 0.6087        | 4.0   | 145  | 0.5493          | 0.7896   |
| 0.5896        | 4.99  | 181  | 0.5028          | 0.7993   |
| 0.6168        | 5.99  | 217  | 0.4787          | 0.8100   |
| 0.5627        | 6.98  | 253  | 0.4373          | 0.8319   |
| 0.5654        | 8.0   | 290  | 0.4324          | 0.8299   |
| 0.5204        | 8.99  | 326  | 0.4130          | 0.8319   |
| 0.5581        | 9.99  | 362  | 0.4264          | 0.8241   |
| 0.5232        | 10.98 | 398  | 0.4074          | 0.8294   |
| 0.483         | 12.0  | 435  | 0.3850          | 0.8445   |
| 0.5208        | 12.99 | 471  | 0.3791          | 0.8489   |
| 0.4937        | 13.99 | 507  | 0.3723          | 0.8528   |
| 0.4436        | 14.98 | 543  | 0.3910          | 0.8440   |
| 0.5169        | 16.0  | 580  | 0.3794          | 0.8465   |
| 0.4394        | 16.99 | 616  | 0.3876          | 0.8440   |
| 0.4616        | 17.99 | 652  | 0.3844          | 0.8465   |
| 0.4983        | 18.98 | 688  | 0.3552          | 0.8591   |
| 0.5295        | 20.0  | 725  | 0.3561          | 0.8547   |
| 0.5121        | 20.99 | 761  | 0.3573          | 0.8537   |
| 0.4379        | 21.99 | 797  | 0.3593          | 0.8576   |
| 0.4653        | 22.98 | 833  | 0.3473          | 0.8601   |
| 0.486         | 24.0  | 870  | 0.3473          | 0.8610   |
| 0.4751        | 24.99 | 906  | 0.3638          | 0.8552   |
| 0.4462        | 25.99 | 942  | 0.3533          | 0.8542   |
| 0.4197        | 26.98 | 978  | 0.3464          | 0.8601   |
| 0.4966        | 28.0  | 1015 | 0.3451          | 0.8649   |
| 0.5004        | 28.99 | 1051 | 0.3634          | 0.8508   |
| 0.4156        | 29.99 | 1087 | 0.3723          | 0.8474   |
| 0.4508        | 30.98 | 1123 | 0.3342          | 0.8669   |
| 0.43          | 32.0  | 1160 | 0.3389          | 0.8639   |
| 0.5004        | 32.99 | 1196 | 0.3416          | 0.8615   |
| 0.4927        | 33.99 | 1232 | 0.3545          | 0.8533   |
| 0.4802        | 34.98 | 1268 | 0.3382          | 0.8610   |
| 0.4334        | 36.0  | 1305 | 0.3480          | 0.8542   |
| 0.4557        | 36.99 | 1341 | 0.3392          | 0.8601   |
| 0.4551        | 37.99 | 1377 | 0.3488          | 0.8542   |
| 0.4643        | 38.98 | 1413 | 0.3424          | 0.8586   |
| 0.513         | 39.72 | 1440 | 0.3433          | 0.8576   |


### Framework versions

- Transformers 4.28.0
- Pytorch 1.8.1+cu111
- Datasets 2.14.5
- Tokenizers 0.13.3

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