# UpsideDownClassifier

This classifier was trained using the [auto-cats-and-dogs](https://huggingface.co/datasets/nateraw/auto-cats-and-dogs) dataset. It was trained over 5 epochs using a pretrained resent18. 

The configuration for the model was 
```
config = {
    "batch_size": 64,
    "num_epochs": 5,
    "lr": 0.005,
    "betas": (0.9, 0.999),
    "eps": 1e-6,
    "lr": 8e-3,
    "do_eval": True
}
```

## Traning Plots

We can see in the figures below the training plots for accuracy and the loss in both, training and validation sets.

### Accuracy Plot
![Accuracy](https://huggingface.co/israfelsr/UpsideDownClassifier/blob/main/accuracy.png)
### Loss Plot
![Loss](https://huggingface.co/israfelsr/UpsideDownClassifier/blob/main/loss.png)

## Some Results

Evaluating on the Test Set, we obtain:
- Accuracy = 0.9696

A batch with some missclassifications can be seen in the picture below.
![Results](https://huggingface.co/israfelsr/UpsideDownClassifier/blob/main/results.png)
{}
region:us
TAGS
#region-us 

# UpsideDownClassifier

This classifier was trained using the auto-cats-and-dogs dataset. It was trained over 5 epochs using a pretrained resent18. 

The configuration for the model was 


## Traning Plots

We can see in the figures below the training plots for accuracy and the loss in both, training and validation sets.

### Accuracy Plot
!Accuracy
### Loss Plot
!Loss

## Some Results

Evaluating on the Test Set, we obtain:
- Accuracy = 0.9696

A batch with some missclassifications can be seen in the picture below.
!Results
# UpsideDownClassifier

This classifier was trained using the auto-cats-and-dogs dataset. It was trained over 5 epochs using a pretrained resent18. 

The configuration for the model was ## Traning Plots

We can see in the figures below the training plots for accuracy and the loss in both, training and validation sets. ### Accuracy Plot
!Accuracy ### Loss Plot
!Loss ## Some Results

Evaluating on the Test Set, we obtain:
- Accuracy = 0.9696

A batch with some missclassifications can be seen in the picture below.
!Results
TAGS
#region-us 
 # UpsideDownClassifier

This classifier was trained using the auto-cats-and-dogs dataset. It was trained over 5 epochs using a pretrained resent18. 

The configuration for the model was ## Traning Plots

We can see in the figures below the training plots for accuracy and the loss in both, training and validation sets. ### Accuracy Plot
!Accuracy ### Loss Plot
!Loss ## Some Results

Evaluating on the Test Set, we obtain:
- Accuracy = 0.9696

A batch with some missclassifications can be seen in the picture below.
!Results
passage: TAGS
#region-us 
# UpsideDownClassifier

This classifier was trained using the auto-cats-and-dogs dataset. It was trained over 5 epochs using a pretrained resent18. 

The configuration for the model was## Traning Plots

We can see in the figures below the training plots for accuracy and the loss in both, training and validation sets.### Accuracy Plot
!Accuracy### Loss Plot
!Loss## Some Results

Evaluating on the Test Set, we obtain:
- Accuracy = 0.9696

A batch with some missclassifications can be seen in the picture below.
!Results