Update README.md
Browse files
README.md
CHANGED
|
@@ -2,28 +2,31 @@
|
|
| 2 |
license: apache-2.0
|
| 3 |
base_model: deepmind/language-perceiver
|
| 4 |
tags:
|
| 5 |
-
-
|
|
|
|
|
|
|
| 6 |
metrics:
|
| 7 |
- f1
|
| 8 |
widget:
|
| 9 |
-
|
| 10 |
-
|
| 11 |
-
|
| 12 |
-
|
| 13 |
-
|
| 14 |
-
|
| 15 |
-
|
| 16 |
-
|
| 17 |
-
|
| 18 |
-
|
| 19 |
-
|
| 20 |
-
|
| 21 |
-
|
| 22 |
-
|
| 23 |
-
|
| 24 |
-
|
| 25 |
-
|
| 26 |
-
|
|
|
|
| 27 |
---
|
| 28 |
|
| 29 |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
|
@@ -38,11 +41,10 @@ It achieves the following results on the evaluation set:
|
|
| 38 |
|
| 39 |
## Model description
|
| 40 |
|
| 41 |
-
## Model description
|
| 42 |
-
|
| 43 |
This classifies one or more **genre** labels in a **multi-label** setting for a given book **title**.
|
| 44 |
|
| 45 |
The 'standard' way of interpreting the predictions is that the predicted labels for a given example are **only the ones with a greater than 50% probability.**
|
|
|
|
| 46 |
## Training procedure
|
| 47 |
|
| 48 |
### Training hyperparameters
|
|
@@ -77,4 +79,4 @@ The following hyperparameters were used during training:
|
|
| 77 |
- Transformers 4.33.3
|
| 78 |
- Pytorch 2.2.0.dev20231001+cu121
|
| 79 |
- Datasets 2.14.5
|
| 80 |
-
- Tokenizers 0.13.3
|
|
|
|
| 2 |
license: apache-2.0
|
| 3 |
base_model: deepmind/language-perceiver
|
| 4 |
tags:
|
| 5 |
+
- book
|
| 6 |
+
- genre
|
| 7 |
+
- book title
|
| 8 |
metrics:
|
| 9 |
- f1
|
| 10 |
widget:
|
| 11 |
+
- text: The Quantum Chip
|
| 12 |
+
example_title: Science Fiction & Fantasy
|
| 13 |
+
- text: One Dollar's Journey
|
| 14 |
+
example_title: Business & Finance
|
| 15 |
+
- text: Timmy The Talking Tree
|
| 16 |
+
example_title: idk fiction
|
| 17 |
+
- text: The Cursed Canvas
|
| 18 |
+
example_title: Arts & Design
|
| 19 |
+
- text: Hoops and Hegel
|
| 20 |
+
example_title: Philosophy & Religion
|
| 21 |
+
- text: Overview of Streams in North Dakota
|
| 22 |
+
example_title: Nature
|
| 23 |
+
- text: Advanced Topology
|
| 24 |
+
example_title: Non-fiction/Math
|
| 25 |
+
- text: Cooking Up Love
|
| 26 |
+
example_title: Food & Cooking
|
| 27 |
+
- text: Dr. Doolittle's Extraplanatary Commute
|
| 28 |
+
example_title: Science & Technology
|
| 29 |
+
pipeline_tag: text-classification
|
| 30 |
---
|
| 31 |
|
| 32 |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
|
|
|
| 41 |
|
| 42 |
## Model description
|
| 43 |
|
|
|
|
|
|
|
| 44 |
This classifies one or more **genre** labels in a **multi-label** setting for a given book **title**.
|
| 45 |
|
| 46 |
The 'standard' way of interpreting the predictions is that the predicted labels for a given example are **only the ones with a greater than 50% probability.**
|
| 47 |
+
|
| 48 |
## Training procedure
|
| 49 |
|
| 50 |
### Training hyperparameters
|
|
|
|
| 79 |
- Transformers 4.33.3
|
| 80 |
- Pytorch 2.2.0.dev20231001+cu121
|
| 81 |
- Datasets 2.14.5
|
| 82 |
+
- Tokenizers 0.13.3
|