Update README.md
Browse files
README.md
CHANGED
|
@@ -35,6 +35,9 @@ model-index:
|
|
| 35 |
- type: accuracy
|
| 36 |
value: 0.9867030994328562
|
| 37 |
name: Accuracy
|
|
|
|
|
|
|
|
|
|
| 38 |
---
|
| 39 |
|
| 40 |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
|
@@ -52,15 +55,37 @@ It achieves the following results on the evaluation set:
|
|
| 52 |
|
| 53 |
## Model description
|
| 54 |
|
| 55 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 56 |
|
| 57 |
## Intended uses & limitations
|
| 58 |
|
| 59 |
-
|
| 60 |
|
| 61 |
## Training and evaluation data
|
| 62 |
|
| 63 |
-
|
| 64 |
|
| 65 |
## Training procedure
|
| 66 |
|
|
@@ -91,4 +116,4 @@ The following hyperparameters were used during training:
|
|
| 91 |
- Transformers 4.41.2
|
| 92 |
- Pytorch 2.3.0+cu121
|
| 93 |
- Datasets 2.19.2
|
| 94 |
-
- Tokenizers 0.19.1
|
|
|
|
| 35 |
- type: accuracy
|
| 36 |
value: 0.9867030994328562
|
| 37 |
name: Accuracy
|
| 38 |
+
language:
|
| 39 |
+
- en
|
| 40 |
+
- uk
|
| 41 |
---
|
| 42 |
|
| 43 |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
|
|
|
| 55 |
|
| 56 |
## Model description
|
| 57 |
|
| 58 |
+
Ukr. Модель була створена як практичне завдання з машиного навчання, це за fine-tuning BERT модель для задачі Named Entity Recognition.
|
| 59 |
+
Датасет який був використан це conll2003, стандат для навчання моделей під задачу Named Entity Recognition, або ще визначення складових мови в реченні.
|
| 60 |
+
Дізнатися як працює модель маєте змогу або через інтерфейс, який надає huggingface, або ж через код
|
| 61 |
+
|
| 62 |
+
from transformers import AutoTokenizer, AutoModelForTokenClassification
|
| 63 |
+
|
| 64 |
+
tokenizer = AutoTokenizer.from_pretrained("CineAI/NER_Pittsburgh_TAA")
|
| 65 |
+
model = AutoModelForTokenClassification.from_pretrained("CineAI/NER_Pittsburgh_TAA")
|
| 66 |
+
|
| 67 |
+
Якщо цікавить чому модель має таку назву, перше це для чого вона для NER, друга складова це назва крутої пісні Pittsburgh третя і остання складова
|
| 68 |
+
це гурт який пісню створив це The Amity Affliction
|
| 69 |
+
|
| 70 |
+
En. The model was created as a practical machine learning task, it is a fine-tuning BERT model for the Named Entity Recognition task.
|
| 71 |
+
The dataset used is conll2003, a standard for training models for the Named Entity Recognition task, or for identifying the components of speech in a sentence.
|
| 72 |
+
You can find out how the model works either through the interface provided by huggingface or through the code
|
| 73 |
+
|
| 74 |
+
from transformers import AutoTokenizer, AutoModelForTokenClassification
|
| 75 |
+
|
| 76 |
+
tokenizer = AutoTokenizer.from_pretrained("CineAI/NER_Pittsburgh_TAA")
|
| 77 |
+
model = AutoModelForTokenClassification.from_pretrained("CineAI/NER_Pittsburgh_TAA")
|
| 78 |
+
|
| 79 |
+
If you are wondering why the model has such a name, the first is why it is for NER, the second component is the name of a cool song Pittsburgh, the third and last component
|
| 80 |
+
is the band that created the song - The Amity Affliction
|
| 81 |
|
| 82 |
## Intended uses & limitations
|
| 83 |
|
| 84 |
+
Everyone can use this model, it is completely free and distributed under the Apache 2.0 licence.
|
| 85 |
|
| 86 |
## Training and evaluation data
|
| 87 |
|
| 88 |
+
Training and assessment data are the same - conll2003
|
| 89 |
|
| 90 |
## Training procedure
|
| 91 |
|
|
|
|
| 116 |
- Transformers 4.41.2
|
| 117 |
- Pytorch 2.3.0+cu121
|
| 118 |
- Datasets 2.19.2
|
| 119 |
+
- Tokenizers 0.19.1
|