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classifier-clinc-MBbase-distilled-optuna – AI Model by Mathildeholst | AlphaNeural AI
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Mathildeholst
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classifier-clinc-MBbase-distilled-optuna
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transformers
safetensors
modernbert
text-classification
generated_from_trainer
answerdotai/ModernBERT-base
finetune
apache-2.0
text-embeddings-inference
endpoints_compatible
us
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classifier-clinc-MBbase-distilled-optuna
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: 0.7741
Accuracy: 0.9535
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: 32
eval_batch_size: 32
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: 6
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
No log
1.0
313
3.4520
0.8368
6.0158
2.0
626
1.4572
0.9303
6.0158
3.0
939
1.0490
0.9461
1.1379
4.0
1252
0.8826
0.9532
0.6026
5.0
1565
0.7999
0.9535
0.6026
6.0
1878
0.7741
0.9535
Framework versions
Transformers 4.57.1
Pytorch 2.8.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1
