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fineweb-nemotron-edu-score – AI Model by lapa-llm | AlphaNeural AI
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fineweb-nemotron-edu-score
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transformers
tensorboard
safetensors
xlm-roberta
text-classification
generated_from_trainer
uk
intfloat/multilingual-e5-base
finetune
mit
text-embeddings-inference
endpoints_compatible
us
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fineweb-nemotron-edu-score
This model is a fine-tuned version of
intfloat/multilingual-e5-base
on an
transferred from English
dataset. It achieves the following results on the evaluation set:
Loss: 0.0489
Precision: 0.9571
Recall: 0.9605
F1 Macro: 0.9588
Accuracy: 0.9632
Model description
This model measure educational value of the given text for humans, as labelled by Nemotron-340B model.
Intended uses & limitations
Data filtering and evaluation of pretraining data at scale.
Training and evaluation data
Take a look at
https://github.com/lapa-llm/lapa-llm/blob/main/pretraining/quality-classifiers/fineweb_hf.py
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
learning_rate: 3e-05
train_batch_size: 32
eval_batch_size: 128
seed: 0
distributed_type: multi-GPU
num_devices: 8
total_train_batch_size: 256
total_eval_batch_size: 1024
optimizer: Use OptimizerNames.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: 4
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1 Macro
Accuracy
No log
0
0
1.0257
0.3334
0.5
0.4001
0.6668
0.0562
1.3793
200
0.0520
0.9537
0.9549
0.9543
0.9593
0.0517
2.7586
400
0.0489
0.9571
0.9605
0.9588
0.9632
Framework versions
Transformers 4.56.1
Pytorch 2.6.0a0+ecf3bae40a.nv25.01
Datasets 4.0.0
Tokenizers 0.22.0
