Comments (2)
This confirms what we learnt for BLEU, too: one should ALWAYS report version numbers (signatures), also for COMET!
Side note: in my MATEO, I added a custom signature for neural metrics like bertscore, bleurt and comet, too. For COMET it looks like this (inspired by sacrebleu):
comet: nrefs:1|bs:1000|seed:12345|c:Unbabel/wmt22-comet-da|version:2.0.1|mateo:1.1.3
where c
stands for the checkpoint used and version
is self-explanatory. Wasn't sure how far one had to go with this because difference in torch, cuda and transformers versions may or may not also lead to difference in results. Hell, even then the CUDA optimisation might lead to different results on different hardware.
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Admittedly the README currently says it requires 3.8, so maybe I installed COMET in the stone age and pip install βupgrade unbabel-comet
never warned me. Anyway I think the score mismatch should not be expected
Your signature is very thoughtful!
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Related Issues (20)
- if tgt is same with src, the score is still high HOT 2
- [QUESTION] Train UnifiedMetric/XCOMET with word level predictions. HOT 1
- Sparsemax not actually used in COMET-KIWI, XCOMET-XL/XXL HOT 4
- Invalid link reference of reference-free model in readme
- Minimizing cpu RAM vs only use GPU RAM HOT 1
- what is the precision when load_from_checkpoint?
- Runtime error when loading wmt23-cometkiwi-da-xl HOT 1
- Different versions of COMET code give different scores with the same model and date.
- [QUESTION] large file scoring HOT 3
- [QUESTION] Splitting big models over multiple GPUs HOT 6
- [QUESTION] Memory footprint HOT 21
- [INPUT] Text Length of Input (source, reference, and hypothesis) HOT 2
- Change the global variable logger to comet_logger HOT 1
- Training script for XCOMET HOT 1
- Safetensors Support
- [QUESTION] OOM when load XCOMET-XXL in A100 with 40G memory for prediction HOT 4
- [QUESTION] why num_layers = num_hidden_layers + 1 HOT 1
- [QUESTION] Comet kiwi architecture HOT 11
- Training data and scripts used for wmt22-cometkiwi-da HOT 3
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