Ezi's picture
Update README.md
bec3c81
|
raw
history blame
3.74 kB
metadata
language: en
tags:
  - token-classification
  - NER
  - Biomedical
  - Chemicals
datasets:
  - BC5CDR-chemicals
  - BC4CHEMD
license: apache-2.0

​ ​

Model Card for biobert Chemical NER

Model Details

Model Description

BioBERT model fine-tuned in NER task with BC5CDR-chemicals and BC4CHEMD corpus.

  • Developed by: librAIry
  • Shared by [Optional]: Alvaro A
  • Model type: Token Classification
  • Language(s) (NLP): More information needed
  • License: Apache 2.0
  • Parent Model: NER
  • Resources for more information:

​ ​

Uses

​

Direct Use

This model can be used for the task of model is lost/undocumented. It was fine-tuned in order to use it in a BioNER/BioNEN system which is available at the GitHub Repo

Downstream Use [Optional]

More information needed.

Out-of-Scope Use

The model should not be used to intentionally create hostile or alienating environments for people.

Bias, Risks, and Limitations

Significant research has explored bias and fairness issues with language models (see, e.g., Sheng et al. (2021) and Bender et al. (2021)). Predictions generated by the model may include disturbing and harmful stereotypes across protected classes; identity characteristics; and sensitive, social, and occupational groups. ​ ​ ​

Recommendations

Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ​

Training Details

Training Data

More information needed

Training Procedure

​

Preprocessing

More information needed

​ ​

Speeds, Sizes, Times

More information needed ​

Evaluation

Testing Data, Factors & Metrics

Testing Data

More information needed

Factors

More information needed

Metrics

More information needed

Results

More information needed ​

Model Examination

More information needed

Environmental Impact

Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

  • Hardware Type: More information needed
    • Fine-tuning process: was done in Google Collab using a TPU.
  • Hours used: More information needed
  • Cloud Provider: More information needed
  • Compute Region: More information needed
  • Carbon Emitted: More information needed

Technical Specifications [optional]

Model Architecture and Objective

​ More information needed

Compute Infrastructure

More information needed

Hardware

More information needed

Software

More information needed.

Citation

​

BibTeX:

More information needed.

Glossary [optional]

More information needed

More Information [optional]

More information needed ​

Model Card Authors [optional]

Alvaro A in collaboration with Ezi Ozoani and the Hugging Face team ​ ​

Model Card Contact

More information needed

How to Get Started with the Model

Use the code below to get started with the model.

Click to expand ​ ```python from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("alvaroalon2/biobert_chemical_ner") model = AutoModelForTokenClassification.from_pretrained("alvaroalon2/biobert_chemical_ner") ```