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# convnext-mlo-512-breat_composition-ordinal

This model is a fine-tuned version of [](https://huggingface.co/) on the preprocessed1024_config dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0275
- Accuracy: {'accuracy': 0.12185929648241206}
- F1: {'f1': 0.05431131019036954}

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy                           | F1                           |
|:-------------:|:-----:|:----:|:---------------:|:----------------------------------:|:----------------------------:|
| 0.0233        | 1.0   | 796  | 0.0269          | {'accuracy': 0.042085427135678394} | {'f1': 0.02019288728149488}  |
| 0.0202        | 2.0   | 1592 | 0.0250          | {'accuracy': 0.09610552763819095}  | {'f1': 0.043839541547277934} |
| 0.0183        | 3.0   | 2388 | 0.0248          | {'accuracy': 0.07977386934673367}  | {'f1': 0.036940081442699245} |
| 0.0163        | 4.0   | 3184 | 0.0259          | {'accuracy': 0.17022613065326633}  | {'f1': 0.07273215244229736}  |
| 0.0144        | 5.0   | 3980 | 0.0258          | {'accuracy': 0.146356783919598}    | {'f1': 0.06383561643835617}  |
| 0.0117        | 6.0   | 4776 | 0.0249          | {'accuracy': 0.0992462311557789}   | {'f1': 0.045142857142857144} |
| 0.0105        | 7.0   | 5572 | 0.0256          | {'accuracy': 0.10238693467336683}  | {'f1': 0.04643874643874644}  |
| 0.0084        | 8.0   | 6368 | 0.0261          | {'accuracy': 0.12185929648241206}  | {'f1': 0.05431131019036954}  |
| 0.0071        | 9.0   | 7164 | 0.0270          | {'accuracy': 0.10238693467336683}  | {'f1': 0.04643874643874644}  |
| 0.0065        | 10.0  | 7960 | 0.0275          | {'accuracy': 0.12185929648241206}  | {'f1': 0.05431131019036954}  |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.12.0
- Datasets 2.1.0
- Tokenizers 0.12.1

{"tags": ["generated_from_trainer"], "datasets": ["preprocessed1024_config"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "convnext-mlo-512-breat_composition-ordinal", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "preprocessed1024_config", "type": "preprocessed1024_config", "args": "default"}, "metrics": [{"type": "accuracy", "value": {"accuracy": 0.12185929648241206}, "name": "Accuracy"}, {"type": "f1", "value": {"f1": 0.05431131019036954}, "name": "F1"}]}]}]}
transformers pytorch convnext image-classification generated_from_trainer dataset:preprocessed1024_config model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #convnext #image-classification #generated_from_trainer #dataset-preprocessed1024_config #model-index #autotrain_compatible #endpoints_compatible #region-us 

convnext-mlo-512-breat\_composition-ordinal
===========================================


This model is a fine-tuned version of [](URL on the preprocessed1024\_config dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0275
* Accuracy: {'accuracy': 0.12185929648241206}
* F1: {'f1': 0.05431131019036954}


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: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10


### Training results



### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0
* Datasets 2.1.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0
* Datasets 2.1.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #convnext #image-classification #generated_from_trainer #dataset-preprocessed1024_config #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0
* Datasets 2.1.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #convnext #image-classification #generated_from_trainer #dataset-preprocessed1024_config #model-index #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10### Training results### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0
* Datasets 2.1.0
* Tokenizers 0.12.1