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---
tags:
- generated_from_trainer
datasets:
- preprocessed1024_config
metrics:
- accuracy
- f1
model-index:
- name: convnext-mlo-512-breat_composition
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: preprocessed1024_config
type: preprocessed1024_config
args: default
metrics:
- name: Accuracy
type: accuracy
value:
accuracy: 0.5785175879396985
- name: F1
type: f1
value:
f1: 0.565251065728165
---
<!-- 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. -->
# convnext-mlo-512-breat_composition
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: 1.1521
- Accuracy: {'accuracy': 0.5785175879396985}
- F1: {'f1': 0.565251065728165}
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------------------------------:|:---------------------------:|
| 1.3433 | 1.0 | 796 | 1.1893 | {'accuracy': 0.4566582914572864} | {'f1': 0.32080438921262083} |
| 1.1242 | 2.0 | 1592 | 1.0867 | {'accuracy': 0.48555276381909546} | {'f1': 0.4061780745199038} |
| 1.0569 | 3.0 | 2388 | 1.1587 | {'accuracy': 0.49120603015075376} | {'f1': 0.40970823779940124} |
| 0.9327 | 4.0 | 3184 | 0.9901 | {'accuracy': 0.5452261306532663} | {'f1': 0.4885626990630958} |
| 0.8723 | 5.0 | 3980 | 0.9824 | {'accuracy': 0.5728643216080402} | {'f1': 0.5365052338942904} |
| 0.7803 | 6.0 | 4776 | 1.0071 | {'accuracy': 0.571608040201005} | {'f1': 0.5246756181464156} |
| 0.7198 | 7.0 | 5572 | 1.0233 | {'accuracy': 0.5741206030150754} | {'f1': 0.5405969058526473} |
| 0.6589 | 8.0 | 6368 | 1.0902 | {'accuracy': 0.5816582914572864} | {'f1': 0.5421523761661359} |
| 0.6055 | 9.0 | 7164 | 1.0980 | {'accuracy': 0.5835427135678392} | {'f1': 0.5601877104043351} |
| 0.5722 | 10.0 | 7960 | 1.1521 | {'accuracy': 0.5785175879396985} | {'f1': 0.565251065728165} |
### Framework versions
- Transformers 4.20.1
- Pytorch 1.12.0
- Datasets 2.1.0
- Tokenizers 0.12.1
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