Update README.md
Browse files
README.md
CHANGED
|
@@ -1,8 +1,8 @@
|
|
| 1 |
---
|
| 2 |
license: mit
|
| 3 |
-
pipeline_tag: fill-mask
|
| 4 |
tags:
|
| 5 |
- code
|
|
|
|
| 6 |
---
|
| 7 |
# Zero-shot text classification (base-sized model) trained with self-supervised tuning
|
| 8 |
|
|
@@ -15,6 +15,7 @@ The model backbone is RoBERTa-base.
|
|
| 15 |
|
| 16 |
## Model description
|
| 17 |
|
|
|
|
| 18 |
The model is tuned with unlabeled data using a learning objective called first sentence prediction (FSP).
|
| 19 |
The FSP task is designed by considering both the nature of the unlabeled corpus and the input/output format of classification tasks.
|
| 20 |
The training and validation sets are constructed from the unlabeled corpus using FSP.
|
|
|
|
| 1 |
---
|
| 2 |
license: mit
|
|
|
|
| 3 |
tags:
|
| 4 |
- code
|
| 5 |
+
- Zero-Shot Classification
|
| 6 |
---
|
| 7 |
# Zero-shot text classification (base-sized model) trained with self-supervised tuning
|
| 8 |
|
|
|
|
| 15 |
|
| 16 |
## Model description
|
| 17 |
|
| 18 |
+
|
| 19 |
The model is tuned with unlabeled data using a learning objective called first sentence prediction (FSP).
|
| 20 |
The FSP task is designed by considering both the nature of the unlabeled corpus and the input/output format of classification tasks.
|
| 21 |
The training and validation sets are constructed from the unlabeled corpus using FSP.
|