Text Classification
Transformers
ONNX
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use albertmartinez/bert-multilingual-sdg-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use albertmartinez/bert-multilingual-sdg-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="albertmartinez/bert-multilingual-sdg-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("albertmartinez/bert-multilingual-sdg-classification") model = AutoModelForSequenceClassification.from_pretrained("albertmartinez/bert-multilingual-sdg-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
5b96a52
1
Parent(s): 896173d
Update
Browse files
README.md
CHANGED
|
@@ -15,4 +15,20 @@ widget:
|
|
| 15 |
|
| 16 |
# albertmartinez/bert-multilingual-sdg-classification
|
| 17 |
|
| 18 |
-
This model (BERT) is for classifying text with respect to the United Nations sustainable development goals (SDG).
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 15 |
|
| 16 |
# albertmartinez/bert-multilingual-sdg-classification
|
| 17 |
|
| 18 |
+
This model (BERT) is for classifying text with respect to the United Nations sustainable development goals (SDG).
|
| 19 |
+
|
| 20 |
+
|
| 21 |
+
### Training results
|
| 22 |
+
|
| 23 |
+
| epoch | eval_loss | eval_accuracy | eval_precision | eval_recall | eval_f1 |
|
| 24 |
+
|:-----:|:------------------:|:------------------:|:------------------:|:------------------:|:------------------:|
|
| 25 |
+
| 1 | 0.932697594165802 | 0.7336408412164803 | 0.7360917875267202 | 0.7336408412164803 | 0.7251914694909984 |
|
| 26 |
+
| 2 | 0.7605898976325989 | 0.777343444609491 | 0.7831176862515112 | 0.777343444609491 | 0.777992037469195 |
|
| 27 |
+
| 3 | 0.7255606651306152 | 0.7918849190837307 | 0.7922937492519824 | 0.7918849190837307 | 0.7897436793752113 |
|
| 28 |
+
| 4 | 0.7620322108268738 | 0.782581502619029 | 0.791463371337951 | 0.782581502619029 | 0.7836557631495363 |
|
| 29 |
+
| 5 | 0.7925569415092468 | 0.7989211164099758 | 0.7987793726148532 | 0.7989211164099758 | 0.7976319242111907 |
|
| 30 |
+
| 6 | 0.8901194930076599 | 0.8008756156672661 | 0.8026922096228485 | 0.8008756156672661 | 0.7999251604304751 |
|
| 31 |
+
| 7 | 0.9644309878349304 | 0.797044797122977 | 0.7998531076533889 | 0.797044797122977 | 0.7979133030034837 |
|
| 32 |
+
| 8 | 1.0754749774932861 | 0.8050973340630131 | 0.8031314135784893 | 0.8050973340630131 | 0.8026788633046699 |
|
| 33 |
+
| 9 | 1.1106163263320923 | 0.8066609334688453 | 0.806263013139723 | 0.8066609334688453 | 0.8061921653404509 |
|
| 34 |
+
| 10 | 1.1396784782409668 | 0.8066609334688453 | 0.8056981354865757 | 0.8066609334688453 | 0.8059943909432397 |
|