# MacBERTh

This model is a Historical Language Model for English coming from the [MacBERTh project](https://macberth.netlify.app/).

The architecture is based on BERT base uncased from the original BERT pre-training codebase. 
The training material comes from different sources including:

- EEBO
- ECCO
- COHA
- CLMET3.1
- EVANS
- Hansard Corpus

with a total word count of approximately 3.9B tokens.

Details and evaluation can be found in the accompanying publications:
- [MacBERTh: Development and Evaluation of a Historically Pre-trained Language Model for English (1450-1950)](https://aclanthology.org/2021.nlp4dh-1.4/)
- [Adapting vs. Pre-training Language Models for Historical Languages](https://doi.org/10.46298/jdmdh.9152)
{"language": ["en"], "license": "mit"}
transformers pytorch bert en license:mit endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #en #license-mit #endpoints_compatible #region-us 

# MacBERTh

This model is a Historical Language Model for English coming from the MacBERTh project.

The architecture is based on BERT base uncased from the original BERT pre-training codebase. 
The training material comes from different sources including:

- EEBO
- ECCO
- COHA
- CLMET3.1
- EVANS
- Hansard Corpus

with a total word count of approximately 3.9B tokens.

Details and evaluation can be found in the accompanying publications:
- MacBERTh: Development and Evaluation of a Historically Pre-trained Language Model for English (1450-1950)
- Adapting vs. Pre-training Language Models for Historical Languages
# MacBERTh

This model is a Historical Language Model for English coming from the MacBERTh project.

The architecture is based on BERT base uncased from the original BERT pre-training codebase. 
The training material comes from different sources including:

- EEBO
- ECCO
- COHA
- CLMET3.1
- EVANS
- Hansard Corpus

with a total word count of approximately 3.9B tokens.

Details and evaluation can be found in the accompanying publications:
- MacBERTh: Development and Evaluation of a Historically Pre-trained Language Model for English (1450-1950)
- Adapting vs. Pre-training Language Models for Historical Languages
TAGS
#transformers #pytorch #bert #en #license-mit #endpoints_compatible #region-us 
 # MacBERTh

This model is a Historical Language Model for English coming from the MacBERTh project.

The architecture is based on BERT base uncased from the original BERT pre-training codebase. 
The training material comes from different sources including:

- EEBO
- ECCO
- COHA
- CLMET3.1
- EVANS
- Hansard Corpus

with a total word count of approximately 3.9B tokens.

Details and evaluation can be found in the accompanying publications:
- MacBERTh: Development and Evaluation of a Historically Pre-trained Language Model for English (1450-1950)
- Adapting vs. Pre-training Language Models for Historical Languages
passage: TAGS
#transformers #pytorch #bert #en #license-mit #endpoints_compatible #region-us 
# MacBERTh

This model is a Historical Language Model for English coming from the MacBERTh project.

The architecture is based on BERT base uncased from the original BERT pre-training codebase. 
The training material comes from different sources including:

- EEBO
- ECCO
- COHA
- CLMET3.1
- EVANS
- Hansard Corpus

with a total word count of approximately 3.9B tokens.

Details and evaluation can be found in the accompanying publications:
- MacBERTh: Development and Evaluation of a Historically Pre-trained Language Model for English (1450-1950)
- Adapting vs. Pre-training Language Models for Historical Languages