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# 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

{"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}}]}]}
timm pytorch tensorboard image-classification generated_from_trainer dataset:beans region:us
TAGS
#timm #pytorch #tensorboard #image-classification #generated_from_trainer #dataset-beans #region-us 

timm-resnet18-beans-test-2
==========================


This model is a fine-tuned version of 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



### Framework versions


* Transformers 4.9.1
* Pytorch 1.9.0
* Datasets 1.11.1.dev0
* Tokenizers 0.10.3



### 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 ### Framework versions


* Transformers 4.9.1
* Pytorch 1.9.0
* Datasets 1.11.1.dev0
* Tokenizers 0.10.3
TAGS
#timm #pytorch #tensorboard #image-classification #generated_from_trainer #dataset-beans #region-us 
 ### 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 ### Framework versions


* Transformers 4.9.1
* Pytorch 1.9.0
* Datasets 1.11.1.dev0
* Tokenizers 0.10.3
passage: TAGS
#timm #pytorch #tensorboard #image-classification #generated_from_trainer #dataset-beans #region-us 
### 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### Framework versions


* Transformers 4.9.1
* Pytorch 1.9.0
* Datasets 1.11.1.dev0
* Tokenizers 0.10.3