danielritchie commited on
Commit
434c27d
·
verified ·
1 Parent(s): 3f3b7d7

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +1 -2
README.md CHANGED
@@ -95,8 +95,7 @@ The model demonstrated significant improvement during training, as shown in the
95
  | mAP50 | 0.089 | 0.598 |
96
  | mAP50-95 | 0.057 | 0.499 |
97
 
98
- Initially, the model would enthusiastically label almost anything as a duck, while only finding a few actual ducks (being correct less than 1% of the time when it claimed to find a duck). The improved model is much more discerning: now, when it says it's found a duck, it's right about half the time. While this training approach reduced overall sensitivity to duck detection, testing in our specific deployment environment showed improved recall, suggesting better alignment with real-world conditions. This increased reliability, combined with better accuracy in placing bounding boxes around actual ducks, makes the final model much more practical for real-world use. Adjustments to hyperparameters provided a wide range of outcomes suggesting significant potential for additional improvement.
99
-
100
  ### Model Statistics
101
  - Layers: 168
102
  - Parameters: 3,005,843
 
95
  | mAP50 | 0.089 | 0.598 |
96
  | mAP50-95 | 0.057 | 0.499 |
97
 
98
+ Initially, the model would enthusiastically label almost anything as a duck (teddy bear), while only finding a few actual ducks - infrequently being correct when it claimed to have found a duck. The improved model is much more discerning: now, when it says it's found a duck, it's more likely to have actually identified a duck. While this training approach reduced overall sensitivity to duck detection, testing in our specific deployment environment showed improved recall under specific circumstances, suggesting better alignment with real-world conditions. This increased reliability, combined with better accuracy in placing bounding boxes around actual ducks, makes the final model much more practical for real-world use. When used in a controlled environmnet the incrase in accuraccy may be offset by the decrease in recall, though environment-specific data would certainly be helpful. Adjustments to hyperparameters provided a wide range of outcomes suggesting significant potential for additional improvement.
 
99
  ### Model Statistics
100
  - Layers: 168
101
  - Parameters: 3,005,843