---
tags:
- image-classification
- timm
- transformers
library_name: timm
license: apache-2.0
---
# Model card for resnext101d_32x4d

This repo is provided with ResNeXt101d_32x4d trained by timm.

## Usage

```python
model = timm.create_model("hf_hub:mjun0812/resnext101d_32x4d", pretrained=True)
```

## Detail

ImageNet-1K results

| top1 | top5 |
| -- | -- |
| 80.9695 | 95.1044 |

config

```python
@register_model
def resnext101d_32x4d(pretrained: bool = False, **kwargs) -> ResNet:
    """Constructs a ResNeXt101d 32x4d model."""
    model_args = dict(
        block=Bottleneck,
        layers=(3, 4, 23, 3),
        cardinality=32,
        base_width=4,
        stem_width=32,
        stem_type="deep",
        avg_down=True,
    )
    return _create_resnet("resnext101d_32x4d", pretrained, **dict(model_args, **kwargs))
```

training command

```bash
torchrun train.py \
    --data-dir ~/workspace/dataset/ImageNet --model resnext101d_32x4d --lr 0.6 --warmup-epochs 5 --epochs 240 \
    --weight-decay 1e-4 --sched cosine --reprob 0.4 --recount 3 --remode pixel --aa rand-m7-mstd0.5-inc1 -b 256 -j 6 --amp --dist-bn reduce
```