lbourdois commited on
Commit
96294f5
1 Parent(s): b20198d

Add multilingual to the language tag

Browse files

Hi! A PR to add multilingual to the language tag to improve the referencing.

Files changed (1) hide show
  1. README.md +7 -6
README.md CHANGED
@@ -1,21 +1,22 @@
1
  ---
2
- language:
3
  - de
4
  - en
 
5
  license: mit
6
  tags:
7
  - sentence_embedding
8
  - search
9
- - pytorch
10
- - xlm-roberta
11
  - roberta
12
  - xlm-r-distilroberta-base-paraphrase-v1
13
  - paraphrase
14
  datasets:
15
  - stsb_multi_mt
16
  metrics:
17
- - Spearmans rank correlation
18
- - cosine similarity
19
  ---
20
 
21
  # Cross English & German RoBERTa for Sentence Embeddings
@@ -71,7 +72,7 @@ We did an automatic hyperparameter search for 33 trials with [Optuna](https://gi
71
  The final model was trained with these hyperparameters on the combination of the train and dev datasets from English, German and the crossings of them. The testset was left for testing.
72
 
73
  # Evaluation
74
- The evaluation has been done on English, German and both languages crossed with the STSbenchmark test data. The evaluation-code is available on [Colab](https://colab.research.google.com/drive/1gtGnKq_dYU_sDYqMohTYVMVpxMJjyH0M?usp=sharing). As the metric for evaluation we use the Spearmans rank correlation between the cosine-similarity of the sentence embeddings and STSbenchmark labels.
75
 
76
  | Model Name | Spearman<br/>German | Spearman<br/>English | Spearman<br/>EN-DE & DE-EN<br/>(cross) |
77
  |---------------------------------------------------------------|-------------------|--------------------|------------------|
 
1
  ---
2
+ language:
3
  - de
4
  - en
5
+ - multilingual
6
  license: mit
7
  tags:
8
  - sentence_embedding
9
  - search
10
+ - pytorch
11
+ - xlm-roberta
12
  - roberta
13
  - xlm-r-distilroberta-base-paraphrase-v1
14
  - paraphrase
15
  datasets:
16
  - stsb_multi_mt
17
  metrics:
18
+ - Spearmans rank correlation
19
+ - cosine similarity
20
  ---
21
 
22
  # Cross English & German RoBERTa for Sentence Embeddings
 
72
  The final model was trained with these hyperparameters on the combination of the train and dev datasets from English, German and the crossings of them. The testset was left for testing.
73
 
74
  # Evaluation
75
+ The evaluation has been done on English, German and both languages crossed with the STSbenchmark test data. The evaluation-code is available on [Colab](https://colab.research.google.com/drive/1gtGnKq_dYU_sDYqMohTYVMVpxMJjyH0M?usp=sharing). As the metric for evaluation we use the Spearmans rank correlation between the cosine-similarity of the sentence embeddings and STSbenchmark labels.
76
 
77
  | Model Name | Spearman<br/>German | Spearman<br/>English | Spearman<br/>EN-DE & DE-EN<br/>(cross) |
78
  |---------------------------------------------------------------|-------------------|--------------------|------------------|