language:
- Python
- PyTorch tags:
- cifar
- cats
- upsidedown license: mit datasets:
- cifar10 metrics:
- Accuracy
- Precision
- Recall
model-index:
- name: CatsNet
results:
- task:
type: image-classification # Required. Example: automatic-speech-recognition
name: Image Classification # Optional. Example: Speech Recognition
dataset:
type: cifar10 # Required. Example: common_voice. Use dataset id from https://hf.co/datasets
name: CIFAR10 # Optional. Example: Common Voice zh-CN
metrics:
- type: Accuracy # Required. Example: wer
value: 0.83 # Required. Example: 20.90
name: Test Accuracy # Optional. Example: Test WER
- type: Precision # Required. Example: wer value: 0.83 # Required. Example: 20.90 name: Test Precision # Optional. Example: Test WER
- type: Recall # Required. Example: wer value: 0.82 # Required. Example: 20.90 name: Test Recall # Optional. Example: Test WER
- type: Accuracy # Required. Example: wer
value: 0.83 # Required. Example: 20.90
name: Test Accuracy # Optional. Example: Test WER
- task:
type: image-classification # Required. Example: automatic-speech-recognition
name: Image Classification # Optional. Example: Speech Recognition
dataset:
type: cifar10 # Required. Example: common_voice. Use dataset id from https://hf.co/datasets
name: CIFAR10 # Optional. Example: Common Voice zh-CN
metrics: