multilingual-e5-small-fineweb2hq-vs-c4-classifier

agentlans/multilingual-e5-small-fineweb2hq-vs-c4-classifier

[!IMPORTANT]
Note: This model is provided for reference and reproducibility, not for standalone use.

This model is a fine-tuned version of agentlans/multilingual-e5-small-aligned-v2 on the agentlans/fineweb2hq-vs-c4 dataset.

The aim is to classify text as higher quality (FineWeb 2 HQ) or lower quality (C4) for AI training.

On the validation set:

• Loss: 0.1983
• Accuracy: 0.9515
• Combined Score: 1.3494
• Num Input Tokens Seen: 122880000

Example

from transformers import pipeline

classifier = pipeline("text-classification", model="agentlans/multilingual-e5-small-fineweb2hq-vs-c4-classifier")
classifier("Your text here.")

Limitations

• Not trained on English data
• Tends to be overly permissive, labelling most texts outside training data as high quality
• May be biased against some text types

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 5e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 3.0

Training results

Framework versions

• Transformers 4.51.3
• Pytorch 2.6.0+cu124
• Datasets 3.2.0
• Tokenizers 0.21.0