Comments (1)
Hello,
We only evaluate the final checkpoint, so we do not have evaluations at intermediate steps. Nonetheless, if loss curves and other training signals are still helpful, here are some logs https://wandb.ai/dogml/datacomp-public-sample
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Related Issues (20)
- 14% of SHA256 hashes not matching HOT 32
- the normal success rate and downloading speed? HOT 1
- `zeroshot_templates` split error for FairFace / UTKFace HOT 9
- Deduplication against evaluation sets HOT 1
- Remove CSAM, if present HOT 5
- Metadata for datacomp-large text-based filter HOT 1
- Pretraining dataset HOT 1
- Frequency of Leaderboard Updates HOT 1
- About update metadata with the corresponding image sample in shards HOT 2
- ModuleNotFoundError: No module named 'training' HOT 2
- Availability of npy indices for large pool
- Average caption length for CommonPool HOT 1
- Downloading Commonpool XLarge
- ImageNet 21k based filtered dataset HOT 1
- Invalid files for Datacomp1B
- Problems in run train.py HOT 3
- Metadata downloading fails and no way to resume the download
- Redundant labels in iWILDCAM eval data
- Label Errors in ImageNet-O Eval Set
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