fluency-scorer – AI Model by tcapelle | AlphaNeural AI

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tcapelle/
fluency-scorer

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text-classification

generated_from_trainer

answerdotai/ModernBERT-base

autotrain_compatible

endpoints_compatible

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fluency-scorer

This model is a fine-tuned version of answerdotai/ModernBERT-base on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.3830
F1: 0.8183
Accuracy: 0.8212
Precision: 0.8171
Recall: 0.8212

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 3e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
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: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Accuracy	Precision	Recall
No log	0	0	0.7214	0.5368	0.5168	0.6201	0.5168
0.5801	1.0	6158	0.4019	0.8069	0.8092	0.8056	0.8092
0.4354	2.0	12316	0.3835	0.8176	0.8212	0.8165	0.8212
0.4089	3.0	18474	0.3830	0.8183	0.8212	0.8171	0.8212

Framework versions

Transformers 4.48.1
Pytorch 2.4.1+cu121
Datasets 3.0.1
Tokenizers 0.21.0