{
  "$type": "site.standard.document",
  "bskyPostRef": {
    "cid": "bafyreigldrmxffgwo6exysh5tjcrdirzws7m4liwbn5g4tzq6k2see5e4m",
    "uri": "at://did:plc:pgryn3ephfd2xgft23qokfzt/app.bsky.feed.post/3mliqig7qy7m2"
  },
  "path": "/t/unet1dmodel-not-converging-on-single-batch/37656#post_5",
  "publishedAt": "2026-05-10T11:13:46.000Z",
  "site": "https://discuss.huggingface.co",
  "textContent": "this is the fix to your exact architecture: UNet1DModel(in_channels = 1, out_channels=1,extra_in_channels=64, down_block_types =\n(‘DownBlock1DNoSkip’, ‘DownBlock1D’, ‘DownBlock1D’,‘AttnDownBlock1D’,‘DownBlock1D’),\nup_block_types = (“UpBlock1D”,“UpBlock1D”, “UpBlock1D”, “AttnUpBlock1D”, “UpBlock1DNoSkip”),\nblock_out_channels = (32, 64, 128, 256, 512), time_embedding_type = “fourier”,layers_per_block = 2, act_fn = “silu”) – i opened an issue on this specific quirk on github as well but it was quickly closed, claiming to be a feature and not a bug",
  "title": "UNet1DModel not converging on single batch"
}