PsyDefDetect_bert-base-uncased_merged_lr-6 – AI Model by C-L-V | AlphaNeural AI

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C-L-V/
PsyDefDetect_bert-base-uncased_merged_lr-6

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text-classification

generated_from_trainer

google-bert/bert-base-uncased

text-embeddings-inference

endpoints_compatible

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PsyDefDetect_bert-base-uncased_merged_lr-6

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

Loss: 0.4590
Accuracy: 0.8874
Macro F1: 0.7942
Weighted F1: 0.8859
Macro Precision: 0.8024
Macro Recall: 0.7868

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-06
train_batch_size: 8
eval_batch_size: 8
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: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Macro F1	Weighted F1	Macro Precision	Macro Recall
0.6462	1.0	187	0.5774	0.8579	0.6683	0.8344	0.7755	0.6363
0.5552	2.0	374	0.5312	0.8901	0.7571	0.8761	0.8601	0.7125
0.4972	3.0	561	0.4701	0.8874	0.7915	0.8851	0.8041	0.7805
0.4659	4.0	748	0.4590	0.8874	0.7942	0.8859	0.8024	0.7868

Framework versions

Transformers 5.0.0
Pytorch 2.10.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2