qikp/qes-2

qikp's Educational Scorer (QES)

🎉 You are looking at QES 2, which is a much stronger model covering a few more domains, and trained on far less data!

QES is a model with a similar purpose to HuggingFaceFW/fineweb-edu-classifier, and is trained on a subset of its data.

Mozilla Firefox includes a model fine-tuned on the same base model as QES for form autofill, so the base model's reliability is proven.

Training data

My in-house qikp/quality-pro dataset was used. Additionally, a padding data collator was used.

Training details

Training took 1 minute and 9 seconds on a single T4 GPU from Google.

Model was trained as a FP32/FP16 hybrid as the Turing architecture does not support bfloat16.

The default batch size and learning rate was used.

The model was trained for 3 epochs.

Usage

For 🤗️, load the model and tokenizer first, then run something like:

model(**tokenizer("This is some example text to classify.", return_tensors="pt", truncation=True, max_length=model.config.max_position_embeddings)).logits.item()

You'll need to multiply the logit by 5 if a 1-5 score is needed in order to be a drop-in replacement to other classifiers.

Limitations

QES 2 is a very strong quality and educational classifier beating many of its competitors.