jonaskoenig commited on
Commit
9c22793
·
1 Parent(s): 72d836e

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +17 -2
README.md CHANGED
@@ -5,6 +5,9 @@ tags:
5
  model-index:
6
  - name: xtremedistil-l6-h256-uncased-future-time-references-D2
7
  results: []
 
 
 
8
  ---
9
 
10
  <!-- This model card has been generated automatically according to the information Keras had access to. You should
@@ -12,9 +15,13 @@ probably proofread and complete it, then remove this comment. -->
12
 
13
  # xtremedistil-l6-h256-uncased-future-time-references-D2
14
 
15
- This model is a fine-tuned version of [microsoft/xtremedistil-l6-h256-uncased](https://huggingface.co/microsoft/xtremedistil-l6-h256-uncased) on an unknown dataset.
16
  It achieves the following results on the evaluation set:
17
-
 
 
 
 
18
 
19
  ## Model description
20
 
@@ -38,7 +45,15 @@ The following hyperparameters were used during training:
38
 
39
  ### Training results
40
 
 
 
 
 
 
 
 
41
 
 
42
 
43
  ### Framework versions
44
 
 
5
  model-index:
6
  - name: xtremedistil-l6-h256-uncased-future-time-references-D2
7
  results: []
8
+ datasets:
9
+ - jonaskoenig/trump_administration_statement
10
+ - jonaskoenig/future-time-refernces-static-filter-D2
11
  ---
12
 
13
  <!-- This model card has been generated automatically according to the information Keras had access to. You should
 
15
 
16
  # xtremedistil-l6-h256-uncased-future-time-references-D2
17
 
18
+ This model is a fine-tuned version of [microsoft/xtremedistil-l6-h256-uncased](https://huggingface.co/microsoft/xtremedistil-l6-h256-uncased) on [jonaskoenig/future-time-refernces-static-filter-D2](https://huggingface.co/datasets/jonaskoenig/future-time-refernces-static-filter-D2) and [jonaskoenig/trump_administration_statement](https://huggingface.co/datasets/jonaskoenig/trump_administration_statement).
19
  It achieves the following results on the evaluation set:
20
+ - Train Loss: 0.0055
21
+ - Train Sparse Categorical Accuracy: 0.9984
22
+ - Validation Loss: 0.0074
23
+ - Validation Sparse Categorical Accuracy: 0.9984
24
+ - Epoch: 4
25
 
26
  ## Model description
27
 
 
45
 
46
  ### Training results
47
 
48
+ | Train Loss | Train Sparse Categorical Accuracy | Validation Loss | Validation Sparse Categorical Accuracy | Epoch |
49
+ |:----------:|:---------------------------------:|:---------------:|:--------------------------------------:|:-----:|
50
+ | 0.0388 | 0.9891 | 0.0154 | 0.9957 | 0 |
51
+ | 0.0133 | 0.9962 | 0.0088 | 0.9975 | 1 |
52
+ | 0.0087 | 0.9974 | 0.0081 | 0.9978 | 2 |
53
+ | 0.0068 | 0.9980 | 0.0074 | 0.9982 | 3 |
54
+ | 0.0055 | 0.9984 | 0.0074 | 0.9984 | 4 |
55
 
56
+ The test accuracy is: 99.81%
57
 
58
  ### Framework versions
59