answerdotai-ModernBERT-base_finetuned_augmented_augmented_deepseek – AI Model by jackmedda | AlphaNeural AI

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jackmedda/
answerdotai-ModernBERT-base_finetuned_augmented_augmented_deepseek

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text-classification

generated_from_trainer

answerdotai/ModernBERT-base

autotrain_compatible

endpoints_compatible

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jackmedda/answerdotai-ModernBERT-base_finetuned_augmented_augmented_deepseek

This model is a fine-tuned version of answerdotai/ModernBERT-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.3360
Accuracy: 0.8824
F1: 0.9231
Precision: 0.9231
Recall: 0.9231

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: 4
eval_batch_size: 4
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: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.6891	1.0	46	0.9745	0.7	0.8235	0.7	1.0
0.5473	2.0	92	0.5183	0.7	0.8235	0.7	1.0
0.3445	3.0	138	0.3540	0.9	0.9333	0.875	1.0
0.1769	4.0	184	0.5051	0.9	0.9333	0.875	1.0
0.0387	5.0	230	0.6412	0.9	0.9333	0.875	1.0
0.0116	6.0	276	0.2695	0.9	0.9333	0.875	1.0
0.0005	7.0	322	0.8522	0.9	0.9333	0.875	1.0
0.0	8.0	368	0.5587	0.9	0.9333	0.875	1.0
0.0	9.0	414	0.5669	0.9	0.9333	0.875	1.0
0.0	10.0	460	0.5103	0.9	0.9333	0.875	1.0
0.0	11.0	506	0.5969	0.9	0.9333	0.875	1.0

Framework versions

Transformers 4.48.3
Pytorch 2.3.0+cu121
Datasets 3.2.0
Tokenizers 0.21.0