HuggingFace Text Classification Training
Budget: $14 – $30 NZD
I’m building a text-classification model and want it trained correctly on Hugging Face, preferably running in Google Colab so everything stays reproducible and shareable. The dataset is ready; what I’m missing is someone who can structure the full training pipeline with the Transformers and Datasets libraries, handle tokenisation choices, set up evaluation metrics, and push the finished model (plus config and training script) to the Hugging Face Hub.
Here’s what I expect by the end:
• A Colab notebook (or Python script) that loads my dataset, fine-tunes an appropriate pretrained model, logs metrics, and saves checkpoints.
• Clear comments explaining each step so I can tweak hyperparameters on my own later.
• A brief readme that outlines environment setup and how to reproduce results.
If you’ve already fine-tuned BERT, RoBERTa, or similar models on Hugging Face and are comfortable troubleshooting Colab runtime quirks, that’s exactly the experience I’m after.
Here’s what I expect by the end:
• A Colab notebook (or Python script) that loads my dataset, fine-tunes an appropriate pretrained model, logs metrics, and saves checkpoints.
• Clear comments explaining each step so I can tweak hyperparameters on my own later.
• A brief readme that outlines environment setup and how to reproduce results.
If you’ve already fine-tuned BERT, RoBERTa, or similar models on Hugging Face and are comfortable troubleshooting Colab runtime quirks, that’s exactly the experience I’m after.