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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: 0.5665829145728644
- name: F1
type: f1
value:
f1: 0.5549950963329491
---
<!-- 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: 1.1801
- Accuracy: {'accuracy': 0.5665829145728644}
- F1: {'f1': 0.5549950963329491}
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------------------------------:|:---------------------------:|
| 1.3412 | 1.0 | 796 | 1.1931 | {'accuracy': 0.4547738693467337} | {'f1': 0.31154642522501674} |
| 1.1149 | 2.0 | 1592 | 1.0845 | {'accuracy': 0.4886934673366834} | {'f1': 0.40829339044510005} |
| 1.0531 | 3.0 | 2388 | 1.1650 | {'accuracy': 0.48304020100502515} | {'f1': 0.38992060973001436} |
| 0.917 | 4.0 | 3184 | 0.9950 | {'accuracy': 0.5452261306532663} | {'f1': 0.50281030200465} |
| 0.8633 | 5.0 | 3980 | 1.0152 | {'accuracy': 0.5552763819095478} | {'f1': 0.511332789082197} |
| 0.7747 | 6.0 | 4776 | 1.0201 | {'accuracy': 0.5703517587939698} | {'f1': 0.523154780871296} |
| 0.7133 | 7.0 | 5572 | 1.0345 | {'accuracy': 0.5640703517587939} | {'f1': 0.5198008328503952} |
| 0.659 | 8.0 | 6368 | 1.0702 | {'accuracy': 0.5785175879396985} | {'f1': 0.5460580312777853} |
| 0.5943 | 9.0 | 7164 | 1.1634 | {'accuracy': 0.5734924623115578} | {'f1': 0.5501266468657362} |
| 0.5699 | 10.0 | 7960 | 1.1801 | {'accuracy': 0.5665829145728644} | {'f1': 0.5549950963329491} |
### Framework versions
- Transformers 4.20.1
- Pytorch 1.12.0
- Datasets 2.1.0
- Tokenizers 0.12.1
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