# Chemical vs Pharmaceutical Domain Document Classifier
Chemical domain language model finetuned on 13K Chemical, and 14K Pharma Wikipedia articles broken into paragraphs.

| Train Loss    | Validation Acc. | Test Acc.|
| ------------- |:-------------: | -----:   |
| 0.17      | 0.928  | 0.927    |
# Dataset
Dataset with splits can be found @ [https://www.kaggle.com/shahrukhkhan/pharma-vs-chemicals-domain-classification](https://www.kaggle.com/shahrukhkhan/pharma-vs-chemicals-domain-classification)

# Label Mappings
LABEL_0 => **"PHARMACEUTICAL"** <br/>
LABEL_1 => **"CHEMICAL"**

## Usage in Transformers

```python
from transformers import AutoTokenizer, AutoModelForSequenceClassification
  
tokenizer = AutoTokenizer.from_pretrained("recobo/chemical-bert-uncased-pharmaceutical-chemical-classifier")

model = AutoModelForSequenceClassification.from_pretrained("recobo/chemical-bert-uncased-pharmaceutical-chemical-classifier")
```
{"language": "en", "tags": ["buy-intent", "sell-intent", "consumer-intent"], "widget": [{"text": "Flutoprazepam (Restas) is a drug which is a benzodiazepine. It was patented in Japan by Sumitomo."}]}
transformers pytorch safetensors bert text-classification buy-intent sell-intent consumer-intent en autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #safetensors #bert #text-classification #buy-intent #sell-intent #consumer-intent #en #autotrain_compatible #endpoints_compatible #has_space #region-us 

Chemical vs Pharmaceutical Domain Document Classifier
=====================================================


Chemical domain language model finetuned on 13K Chemical, and 14K Pharma Wikipedia articles broken into paragraphs.



Dataset
=======


Dataset with splits can be found @ URL


Label Mappings
==============


LABEL\_0 => "PHARMACEUTICAL"   

LABEL\_1 => "CHEMICAL"


Usage in Transformers
---------------------



TAGS
#transformers #pytorch #safetensors #bert #text-classification #buy-intent #sell-intent #consumer-intent #en #autotrain_compatible #endpoints_compatible #has_space #region-us 

passage: TAGS
#transformers #pytorch #safetensors #bert #text-classification #buy-intent #sell-intent #consumer-intent #en #autotrain_compatible #endpoints_compatible #has_space #region-us 
