Dear community, 

I ran phyml on a gene family to build a tree. Looking at the results, I'm a bit worried about the log-likelihood value: it's -754, which means the likelihood is almost zero! Does this mean that the program has little confidence in the estimated parameters or the tree topology? I was wondering if I'm understanding this incorrectly. 

Thank you so much!!

```

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                                  ---  PhyML 3.3.20190909  ---                                             
                              http://www.atgc-montpellier.fr/phyml                                          
                             Copyright CNRS - Universite Montpellier                                 
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. Sequence filename: 			exon3_wb_aligned_phy
. Data set: 				#1
. Initial tree: 			BioNJ
. Model of nucleotides substitution: 	GTR
. Number of taxa: 			52
. Log-likelihood: 			-754.13849
. Unconstrained log-likelihood: 	-348.41766
. Composite log-likelihood: 		-6438.01266
. Parsimony: 				119
. Tree size: 				1.35199
. Discrete gamma model: 		Yes
  - Number of classes: 			4
  - Gamma shape parameter: 		1.901
  - Relative rate in class 1: 		0.28116 [freq=0.250000] 		
  - Relative rate in class 2: 		0.64406 [freq=0.250000] 		
  - Relative rate in class 3: 		1.06730 [freq=0.250000] 		
  - Relative rate in class 4: 		2.00748 [freq=0.250000] 		
. Nucleotides frequencies:
  - f(A)=  0.37232
  - f(C)=  0.24092
  - f(G)=  0.17327
  - f(T)=  0.21350
. GTR relative rate parameters :
  A <-> C    0.82212
  A <-> G    1.82689
  A <-> T    0.53724
  C <-> G    0.17829
  C <-> T    2.00016
  G <-> T    1.00000
. Instantaneous rate matrix : 
  [A---------C---------G---------T------]
  -0.82453   0.25951   0.41474   0.15028  
   0.40104  -1.00102   0.04048   0.55950  
   0.89119   0.05628  -1.22720   0.27973  
   0.26208   0.63136   0.22702  -1.12046  


. Run ID:				none
. Random seed:				1625516914
. Subtree patterns aliasing:		no
. Version:				3.3.20190909
. Time used:				0h0m4s (4 seconds)

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 Suggested citations:
 S. Guindon, JF. Dufayard, V. Lefort, M. Anisimova, W. Hordijk, O. Gascuel
 "New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0."
 Systematic Biology. 2010. 59(3):307-321.

 S. Guindon & O. Gascuel
 "A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood"
 Systematic Biology. 2003. 52(5):696-704.
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```
The principle of maximum likelihood is to choose the tree which makes the data most probable. As tree probabilities are usually tiny, especially for large datasets, we express them as ln(P), which is the log likelihood (LL). LL is a negative number (log function is negative in the 0-1 range), and the best it can be is 0 (when the probability is 1).

Seems like you have a smallish tree, and the LL you obtained is appropriate. As of this writing I am monitoring an ongoing large tree that has `LL=-978001.783`, so you are golden. LL values are comparable for the same dataset (alignment), but not between different datasets. Higher LL is better.