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---
tags:
- image-classification
- timm
- generated_from_trainer
datasets:
- beans
metrics:
- accuracy
model_index:
- name: timm-resnet18-beans-test-2
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: beans
type: beans
args: default
metric:
name: Accuracy
type: accuracy
value: 0.5789473684210527
base_model: resnet18
---
<!-- 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. -->
# timm-resnet18-beans-test-2
This model is a fine-tuned version of [resnet18](https://huggingface.co/resnet18) on the beans dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3225
- Accuracy: 0.5789
## 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: 0.001
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2601 | 0.02 | 5 | 2.8349 | 0.5113 |
| 1.8184 | 0.04 | 10 | 1.3225 | 0.5789 |
### Framework versions
- Transformers 4.9.1
- Pytorch 1.9.0
- Datasets 1.11.1.dev0
- Tokenizers 0.10.3
|