system
HF staff
commited on
Commit
d4c19e5
1 Parent(s): 4852b50

Commit From AutoTrain

Browse files
Files changed (4) hide show
  1. .gitattributes +3 -0
  2. README.md +50 -0
  3. config.json +1 -0
  4. model.joblib +3 -0
.gitattributes CHANGED
@@ -25,3 +25,6 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
25
  *.zip filter=lfs diff=lfs merge=lfs -text
26
  *.zstandard filter=lfs diff=lfs merge=lfs -text
27
  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
 
25
  *.zip filter=lfs diff=lfs merge=lfs -text
26
  *.zstandard filter=lfs diff=lfs merge=lfs -text
27
  *tfevents* filter=lfs diff=lfs merge=lfs -text
28
+ *.bin.* filter=lfs diff=lfs merge=lfs -text
29
+ *.tar.gz filter=lfs diff=lfs merge=lfs -text
30
+ *.pkl filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,50 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ tags:
3
+ - autotrain
4
+ - tabular
5
+ - classification
6
+ - tabular-classification
7
+ datasets:
8
+ - abhishek/autotrain-data-iris-train
9
+ co2_eq_emissions: 0.0006300767567816624
10
+ ---
11
+
12
+ # Model Trained Using AutoTrain
13
+
14
+ - Problem type: Multi-class Classification
15
+ - Model ID: 9705273
16
+ - CO2 Emissions (in grams): 0.0006300767567816624
17
+
18
+ ## Validation Metrics
19
+
20
+ - Loss: 0.15987505325856152
21
+ - Accuracy: 0.9
22
+ - Macro F1: 0.899749373433584
23
+ - Micro F1: 0.9
24
+ - Weighted F1: 0.8997493734335841
25
+ - Macro Precision: 0.9023569023569024
26
+ - Micro Precision: 0.9
27
+ - Weighted Precision: 0.9023569023569025
28
+ - Macro Recall: 0.9
29
+ - Micro Recall: 0.9
30
+ - Weighted Recall: 0.9
31
+
32
+ ## Usage
33
+
34
+ ```python
35
+ import json
36
+ import joblib
37
+ import pandas as pd
38
+
39
+ model = joblib.load('model.joblib')
40
+ config = json.load(open('config.json'))
41
+
42
+ features = config['features']
43
+
44
+ # data = pd.read_csv("data.csv")
45
+ data = data[features]
46
+ data.columns = ["feat_" + str(col) for col in data.columns]
47
+
48
+ predictions = model.predict(data) # or model.predict_proba(data)
49
+
50
+ ```
config.json ADDED
@@ -0,0 +1 @@
 
1
+ {"features": ["SepalLengthCm", "SepalWidthCm", "PetalLengthCm", "PetalWidthCm"], "targets": ["target"], "model_type": "logistic_regression", "target_mapping": {"Iris-setosa": 0, "Iris-versicolor": 1, "Iris-virginica": 2}}
model.joblib ADDED
@@ -0,0 +1,3 @@
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c7a75c36f87985171a1e5acae52a7e09a68b6dfff260fb7ec568267b747ca19b
3
+ size 3338