narugo commited on
Commit
a0e053e
·
1 Parent(s): 9aca33f

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +16 -1
README.md CHANGED
@@ -7,4 +7,19 @@ metrics:
7
  pipeline_tag: feature-extraction
8
  tags:
9
  - art
10
- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
7
  pipeline_tag: feature-extraction
8
  tags:
9
  - art
10
+ ---
11
+
12
+ | Model | F1 Score | Precision | Recall | Threshold | Cluster 2 | Cluster Free |
13
+ |:-----------------------------------:|:----------:|:-----------:|:--------:|:-----------:|:-----------:|:--------------:|
14
+ | ccip-caformer-2-randaug-pruned_fp32 | 0.78561 | 0.800148 | 0.771592 | 0.171053 | 0.686617 | 0.728195 |
15
+ | ccip-caformer-23_randaug_fp32 | 0.81625 | 0.854134 | 0.781585 | 0.136797 | 0.745697 | 0.8068 |
16
+ | ccip-caformer-24-randaug-pruned | 0.917211 | 0.933481 | 0.901499 | 0.178475 | 0.890366 | 0.922375 |
17
+ | ccip-caformer-2_fp32 | 0.755125 | 0.790172 | 0.723055 | 0.141275 | 0.64977 | 0.718516 |
18
+ | ccip-caformer-4_fp32 | 0.844967 | 0.870553 | 0.820842 | 0.18367 | 0.795565 | 0.868133 |
19
+ | ccip-caformer-5_fp32 | 0.864363 | 0.90155 | 0.830121 | 0.183973 | 0.792051 | 0.862289 |
20
+ | ccip-caformer-6-randaug-pruned_fp32 | 0.878403 | 0.893648 | 0.863669 | 0.195122 | 0.810176 | 0.897904 |
21
+ | ccip-caformer_query-12 | 0.823928 | 0.871122 | 0.781585 | 0.141308 | 0.787237 | 0.809426 |
22
+
23
+ * The calculation of `F1 Score`, `Precision`, and `Recall` considers "the characters in both images are the same" as a positive case. `Threshold` is determined by finding the maximum value on the F1 Score curve.
24
+ * `Cluster_2` represents the approximate optimal clustering solution obtained by tuning the eps value in DBSCAN clustering algorithm with min_samples set to `2`, and evaluating the similarity between the obtained clusters and the true distribution using the `random_adjust_score`.
25
+ * `Cluster_Free` represents the approximate optimal solution obtained by tuning the `max_eps` and `min_samples` values in the OPTICS clustering algorithm, and evaluating the similarity between the obtained clusters and the true distribution using the `random_adjust_score`.