modernbert-base-optuna_clinc – AI Model by pradervonsky | AlphaNeural AI

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pradervonsky/
modernbert-base-optuna_clinc

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text-classification

generated_from_trainer

answerdotai/ModernBERT-base

text-embeddings-inference

endpoints_compatible

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modernbert-base-optuna_clinc

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: 0.2146
Accuracy: 0.9513

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: 2e-05
train_batch_size: 48
eval_batch_size: 48
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 8

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
2.2361	1.0	318	0.5611	0.8777
0.2099	2.0	636	0.3026	0.9316
0.0641	3.0	954	0.2455	0.9461
0.0315	4.0	1272	0.2290	0.9497
0.0227	5.0	1590	0.2206	0.9513
0.0196	6.0	1908	0.2184	0.95
0.0179	7.0	2226	0.2158	0.9519
0.0172	8.0	2544	0.2146	0.9513

Framework versions

Transformers 4.57.1
Pytorch 2.8.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1