This article will guide you through understanding and using the w11w0-indo-gpt2-small-instruct model. This model is a fine-tuned version of the base model on the cahyaalpaca-id-cleaned dataset, and it’s designed for specific tasks that involve natural language processing.
Model Description
As a fine-tuned version of w11woindo-gpt2-small, this model specializes in generating responses based on user prompts. Although the thorough descriptions and intended use cases are still under development, it is important to note the simplified interaction format:
- Pengguna: insert user prompt here
- Asisten: This is the model’s generated response.
Understanding Limitations
One of the limitations noted for this model is its difficulty in comprehending prompts. This means that while it may generate answers, those answers can sometimes reflect misunderstandings of the inputs.
Training and Evaluation Data
Currently, the specifics about the training and evaluation data are limited. It’s advisable to stay updated on the latest research to fully understand the effectiveness of this model.
Training Procedure and Hyperparameters
To make the magic happen, the model underwent a careful training process using the following hyperparameters:
- Learning Rate: 2e-05
- Train Batch Size: 8
- Eval Batch Size: 8
- Seed: 42
- Optimizer: Adam with
betas=(0.9,0.999)andepsilon=1e-08 - Learning Rate Scheduler: Linear
- Number of Epochs: 1
Framework Versions
The model was built using the following frameworks:
- Transformers: 4.39.3
- Pytorch: 2.1.2
- Datasets: 2.19.0
- Tokenizers: 0.15.2
Troubleshooting Ideas
If you encounter issues when implementing this model, consider the following troubleshooting tips:
- Ensure the environment is set up with the correct versions of the specified libraries.
- Double-check the prompt format and structure to enhance response accuracy.
- Consider tuning the hyperparameters if results are not as expected.
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Conclusion
At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.