Update README.md
Browse files
README.md
CHANGED
|
@@ -10,11 +10,10 @@ metrics:
|
|
| 10 |
model-index:
|
| 11 |
- name: roberta-base-Tweet_About_Disaster_Or_Not
|
| 12 |
results: []
|
|
|
|
|
|
|
| 13 |
---
|
| 14 |
|
| 15 |
-
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 16 |
-
should probably proofread and complete it, then remove this comment. -->
|
| 17 |
-
|
| 18 |
# roberta-base-Tweet_About_Disaster_Or_Not
|
| 19 |
|
| 20 |
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
|
|
@@ -27,15 +26,28 @@ It achieves the following results on the evaluation set:
|
|
| 27 |
|
| 28 |
## Model description
|
| 29 |
|
| 30 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 31 |
|
| 32 |
## Intended uses & limitations
|
| 33 |
|
| 34 |
-
|
|
|
|
|
|
|
| 35 |
|
| 36 |
## Training and evaluation data
|
| 37 |
|
| 38 |
-
|
| 39 |
|
| 40 |
## Training procedure
|
| 41 |
|
|
@@ -66,4 +78,4 @@ The following hyperparameters were used during training:
|
|
| 66 |
- Transformers 4.26.1
|
| 67 |
- Pytorch 1.13.1
|
| 68 |
- Datasets 2.9.0
|
| 69 |
-
- Tokenizers 0.12.1
|
|
|
|
| 10 |
model-index:
|
| 11 |
- name: roberta-base-Tweet_About_Disaster_Or_Not
|
| 12 |
results: []
|
| 13 |
+
language:
|
| 14 |
+
- en
|
| 15 |
---
|
| 16 |
|
|
|
|
|
|
|
|
|
|
| 17 |
# roberta-base-Tweet_About_Disaster_Or_Not
|
| 18 |
|
| 19 |
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
|
|
|
|
| 26 |
|
| 27 |
## Model description
|
| 28 |
|
| 29 |
+
This is a binary classification model to determine if tweet input samples are about a disaster or not.
|
| 30 |
+
|
| 31 |
+
For more information on how it was created, check out the following link: https://github.com/DunnBC22/NLP_Projects/blob/main/Binary%20Classification/Transformer%20Comparison/Is%20This%20Tweet%20Referring%20to%20a%20Disaster%20or%20Not%3F%20-%20RoBERTa.ipynb
|
| 32 |
+
|
| 33 |
+
### Associated Projects
|
| 34 |
+
This project is part of a comparison of multiple transformers. The others can be found at the following links:
|
| 35 |
+
|
| 36 |
+
- https://huggingface.co/DunnBC22/deberta-v3-small-Tweet_About_Disaster_Or_Not
|
| 37 |
+
- https://huggingface.co/DunnBC22/albert-base-v2-Tweet_About_Disaster_Or_Not
|
| 38 |
+
- https://huggingface.co/DunnBC22/electra-base-emotion-Tweet_About_Disaster_Or_Not
|
| 39 |
+
- https://huggingface.co/DunnBC22/ernie-2.0-base-en-Tweet_About_Disaster_Or_Not
|
| 40 |
+
- https://huggingface.co/DunnBC22/distilbert-base-uncased-Tweet_About_Disaster_Or_Not
|
| 41 |
|
| 42 |
## Intended uses & limitations
|
| 43 |
|
| 44 |
+
This model is intended to demonstrate my ability to solve a complex problem using technology.
|
| 45 |
+
|
| 46 |
+
The main limitation is the quality of the data source.
|
| 47 |
|
| 48 |
## Training and evaluation data
|
| 49 |
|
| 50 |
+
Dataset Source: https://www.kaggle.com/datasets/vstepanenko/disaster-tweets
|
| 51 |
|
| 52 |
## Training procedure
|
| 53 |
|
|
|
|
| 78 |
- Transformers 4.26.1
|
| 79 |
- Pytorch 1.13.1
|
| 80 |
- Datasets 2.9.0
|
| 81 |
+
- Tokenizers 0.12.1
|