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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- beans
metrics:
- accuracy
model-index:
- name: convnext-tiny-finetuned-beans
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: beans
type: beans
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.9609375
- task:
type: image-classification
name: Image Classification
dataset:
name: beans
type: beans
config: default
split: test
metrics:
- name: Accuracy
type: accuracy
value: 0.9609375
verified: true
- name: Precision Macro
type: precision
value: 0.9652777777777778
verified: true
- name: Precision Micro
type: precision
value: 0.9609375
verified: true
- name: Precision Weighted
type: precision
value: 0.9650065104166667
verified: true
- name: Recall Macro
type: recall
value: 0.9608711701734958
verified: true
- name: Recall Micro
type: recall
value: 0.9609375
verified: true
- name: Recall Weighted
type: recall
value: 0.9609375
verified: true
- name: F1 Macro
type: f1
value: 0.9615067076130842
verified: true
- name: F1 Micro
type: f1
value: 0.9609375
verified: true
- name: F1 Weighted
type: f1
value: 0.9613965275467993
verified: true
- name: loss
type: loss
value: 0.14331591129302979
verified: true
---
<!-- 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-tiny-finetuned-beans
This model is a fine-tuned version of [facebook/convnext-tiny-224](https://huggingface.co/facebook/convnext-tiny-224) on the beans dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1255
- Accuracy: 0.9609
## 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: 32
- eval_batch_size: 32
- seed: 7171
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 37 | 0.6175 | 0.8828 |
| No log | 2.0 | 74 | 0.2307 | 0.9609 |
| 0.5237 | 3.0 | 111 | 0.1406 | 0.9531 |
| 0.5237 | 4.0 | 148 | 0.1165 | 0.9688 |
| 0.5237 | 5.0 | 185 | 0.1255 | 0.9609 |
### Framework versions
- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.1.0
- Tokenizers 0.12.1
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