Update README.md
#1
by
z-dickson
- opened
README.md
CHANGED
@@ -13,12 +13,17 @@ model-index:
|
|
13 |
|
14 |
This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on a dataset of 30k newspaper headlines in German, Polish, English, Dutch and Spanish. The dataset contains 6k headlines in each of the five languages. The newspapers used are as follows:
|
15 |
|
16 |
-
|
17 |
-
|
18 |
-
|
19 |
-
|
|
|
20 |
|
|
|
21 |
|
|
|
|
|
|
|
22 |
|
23 |
|
24 |
It achieves the following results on the evaluation set:
|
@@ -28,19 +33,6 @@ It achieves the following results on the evaluation set:
|
|
28 |
- Validation Sparse Categorical Accuracy: 0.6434
|
29 |
- Epoch: 4
|
30 |
|
31 |
-
## Model description
|
32 |
-
|
33 |
-
More information needed
|
34 |
-
|
35 |
-
## Intended uses & limitations
|
36 |
-
|
37 |
-
Newpaper headline classification
|
38 |
-
|
39 |
-
## Training and evaluation data
|
40 |
-
|
41 |
-
More information needed
|
42 |
-
|
43 |
-
## Training procedure
|
44 |
|
45 |
### Training hyperparameters
|
46 |
|
@@ -64,3 +56,4 @@ The following hyperparameters were used during training:
|
|
64 |
- Transformers 4.26.0
|
65 |
- TensorFlow 2.9.2
|
66 |
- Tokenizers 0.13.2
|
|
|
|
13 |
|
14 |
This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on a dataset of 30k newspaper headlines in German, Polish, English, Dutch and Spanish. The dataset contains 6k headlines in each of the five languages. The newspapers used are as follows:
|
15 |
|
16 |
+
Polish: Fakt, Rzeczpospolita, Gazeta Wyborcza
|
17 |
+
English: The Times, The Guardian, The Sun
|
18 |
+
Dutch: De Telegraaf, NRC, Volkskrant
|
19 |
+
Spanish: El Mundo, El Pais, ABC
|
20 |
+
German: Suddeutsche Zeitung, De Welt, Bild
|
21 |
|
22 |
+
coding scheme:
|
23 |
|
24 |
+
- "LABEL_0": negative,
|
25 |
+
- "LABEL_1": neutral,
|
26 |
+
- "LABEL_2": "positive"
|
27 |
|
28 |
|
29 |
It achieves the following results on the evaluation set:
|
|
|
33 |
- Validation Sparse Categorical Accuracy: 0.6434
|
34 |
- Epoch: 4
|
35 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
36 |
|
37 |
### Training hyperparameters
|
38 |
|
|
|
56 |
- Transformers 4.26.0
|
57 |
- TensorFlow 2.9.2
|
58 |
- Tokenizers 0.13.2
|
59 |
+
|