GEITje 7B
GEITje 7B is a powerful Dutch language model with 7 billion parameters, built on top of Mistral 7B. What sets it apart is its further training on 10 billion tokens of Dutch text, making it a go-to choice for tasks that require in-depth knowledge of the Dutch language. With a context length of 8,192 tokens, GEITje 7B can handle complex tasks with ease. Its unique architecture allows it to outperform larger models in certain benchmarks, making it a remarkable choice for those who need a reliable and efficient language model for Dutch language tasks.
Table of Contents
Model Overview
The GEITje-7B model is a powerful tool for understanding and generating Dutch text. With 7 billion parameters
and training on 10 billion tokens
of Dutch text, it has become a highly skilled language model.
Capabilities
What can it do?
- Understand Dutch text: It can comprehend and analyze Dutch text with high accuracy.
- Generate Dutch text: The model can create coherent and natural-sounding Dutch text based on a given prompt or topic.
- Answer questions: It can respond to questions on a wide range of topics, from general knowledge to specific domains.
How does it compare to other models?
- Outperforms Llama 2 13B: According to the creators, its base model, Mistral 7B, performs better than Llama 2 13B on all English-language benchmarks tested.
- Unique features: It has a context length of
8,192 tokens
, allowing it to process and understand longer pieces of text.
Training and Performance
Training Procedure
The model was trained using the following hyperparameters:
Hyperparameter | Value |
---|---|
Learning Rate | 2e-05 |
Train Batch Size | 2 |
Eval Batch Size | 2 |
Seed | 42 |
Distributed Type | multi-GPU |
Num Devices | 8 |
Gradient Accumulation Steps | 8 |
Total Train Batch Size | 128 |
Total Eval Batch Size | 16 |
Optimizer | Adam with betas=(0.9,0.999) and epsilon=1e-08 |
LR Scheduler Type | cosine |
LR Scheduler Warmup Steps | 953 |
Training Steps | 9536 |
Training Results
The training results are shown in the table below:
Epoch | Step | Validation Loss |
---|---|---|
1 | 199 | 1.7673 |
2 | 398 | 1.6880 |
3 | 597 | 1.6429 |
… | … | … |
Note that the training loss decreases over time, indicating that the model is learning and improving its performance on the validation set.
Limitations
While the model is powerful, it’s not perfect. Let’s explore some of its limitations.
Language Limitations
- It may struggle with:
- Idioms and colloquialisms
- Sarcasm and humor
- Highly technical or specialized language
- It’s not perfect in understanding:
- Nuances of human language
- Context-dependent expressions
- Subtle differences in meaning
Technical Limitations
- It has a context length of
8,192 tokens
, which means it can process a limited amount of text at a time. This can lead to:- Incomplete or inaccurate responses for very long inputs
- Difficulty in understanding complex, multi-step conversations
Format and Usage
Supported Data Formats
- Text: The model accepts input in the form of text sequences. You can feed it a sentence, a paragraph, or even a whole article.
- Tokens: The model uses a tokenizer to split the input text into individual tokens. These tokens are then used to generate the output.
Input Requirements
- Context Length: The model has a context length of
8,192 tokens
. This means it can handle input sequences of up to8,192 tokens
. - Batch Size: The model uses a batch size of
2
during training. This means it processes2
input sequences at a time.
Output Format
- Text: The model generates output in the form of text sequences.
- Tokenized Output: The output is tokenized, meaning it’s split into individual tokens.
Example Use Cases
- Language translation: The model can be used to translate Dutch text into other languages or vice versa.
- Text summarization: The model can summarize long pieces of Dutch text into concise and meaningful summaries.
- Chatbots: The model can be integrated into chatbots to provide more accurate and informative responses to user queries.
Overall, the GEITje-7B model is a powerful tool for anyone working with Dutch text, offering a range of capabilities and features that make it an attractive choice for various applications.