
<!-- 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. -->

# Output-prova_melanoma

This model is a fine-tuned version of [UnipaPolitoUnimore/vit-large-patch32-384-melanoma](https://huggingface.co/UnipaPolitoUnimore/vit-large-patch32-384-melanoma) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2202
- Accuracy: 0.9467

## 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: 1.5e-05
- 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: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4501        | 1.0   | 47   | 0.2094          | 0.9667   |
| 0.5554        | 2.0   | 94   | 0.2010          | 0.9733   |
| 0.5299        | 3.0   | 141  | 0.1595          | 0.9733   |
| 0.0854        | 4.0   | 188  | 0.1529          | 0.9667   |
| 0.2766        | 5.0   | 235  | 0.1466          | 0.9667   |
| 0.3158        | 6.0   | 282  | 0.1916          | 0.96     |
| 0.1322        | 7.0   | 329  | 0.1924          | 0.9733   |
| 0.065         | 8.0   | 376  | 0.1905          | 0.9533   |
| 0.1565        | 9.0   | 423  | 0.2025          | 0.9467   |
| 0.1296        | 10.0  | 470  | 0.2367          | 0.9333   |
| 0.2448        | 11.0  | 517  | 0.2255          | 0.94     |
| 0.067         | 12.0  | 564  | 0.2315          | 0.94     |
| 0.0764        | 13.0  | 611  | 0.2479          | 0.9467   |
| 0.1472        | 14.0  | 658  | 0.2599          | 0.9333   |
| 0.0483        | 15.0  | 705  | 0.1911          | 0.9533   |
| 0.0961        | 16.0  | 752  | 0.1869          | 0.9533   |
| 0.1146        | 17.0  | 799  | 0.2355          | 0.9333   |
| 0.2117        | 18.0  | 846  | 0.1930          | 0.94     |
| 0.2859        | 19.0  | 893  | 0.1902          | 0.9467   |
| 0.0798        | 20.0  | 940  | 0.2436          | 0.9333   |
| 0.16          | 21.0  | 987  | 0.2341          | 0.94     |
| 0.1968        | 22.0  | 1034 | 0.3552          | 0.9067   |
| 0.1049        | 23.0  | 1081 | 0.2541          | 0.9267   |
| 0.1102        | 24.0  | 1128 | 0.1839          | 0.9467   |
| 0.3039        | 25.0  | 1175 | 0.2269          | 0.9333   |
| 0.1188        | 26.0  | 1222 | 0.2063          | 0.9533   |
| 0.2008        | 27.0  | 1269 | 0.1972          | 0.94     |
| 0.1113        | 28.0  | 1316 | 0.2157          | 0.94     |
| 0.1377        | 29.0  | 1363 | 0.2031          | 0.9533   |
| 0.042         | 30.0  | 1410 | 0.2124          | 0.9533   |
| 0.0841        | 31.0  | 1457 | 0.2174          | 0.94     |
| 0.046         | 32.0  | 1504 | 0.2136          | 0.9467   |
| 0.1309        | 33.0  | 1551 | 0.1981          | 0.96     |
| 0.1207        | 34.0  | 1598 | 0.2334          | 0.94     |
| 0.1216        | 35.0  | 1645 | 0.2238          | 0.94     |
| 0.0518        | 36.0  | 1692 | 0.2441          | 0.9467   |
| 0.0852        | 37.0  | 1739 | 0.2243          | 0.9467   |
| 0.0853        | 38.0  | 1786 | 0.2028          | 0.9533   |
| 0.055         | 39.0  | 1833 | 0.2124          | 0.9467   |
| 0.0646        | 40.0  | 1880 | 0.2202          | 0.9467   |


### Framework versions

- Transformers 4.30.0.dev0
- Pytorch 1.13.1+cu116
- Datasets 2.11.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "model-index": [{"name": "Output-prova_melanoma", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "train", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.9466666666666667, "name": "Accuracy"}]}]}]}
transformers pytorch tensorboard vit image-classification generated_from_trainer dataset:imagefolder license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #vit #image-classification #generated_from_trainer #dataset-imagefolder #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 

Output-prova\_melanoma
======================


This model is a fine-tuned version of UnipaPolitoUnimore/vit-large-patch32-384-melanoma on the imagefolder dataset.
It achieves the following results on the evaluation set:


* Loss: 0.2202
* Accuracy: 0.9467


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: 1.5e-05
* 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: 40


### Training results



### Framework versions


* Transformers 4.30.0.dev0
* Pytorch 1.13.1+cu116
* Datasets 2.11.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1.5e-05
* 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: 40 ### Training results ### Framework versions


* Transformers 4.30.0.dev0
* Pytorch 1.13.1+cu116
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #vit #image-classification #generated_from_trainer #dataset-imagefolder #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1.5e-05
* 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: 40 ### Training results ### Framework versions


* Transformers 4.30.0.dev0
* Pytorch 1.13.1+cu116
* Datasets 2.11.0
* Tokenizers 0.13.3