PsyDefDetect_bert-base-uncased_unmerged_lr-4 – AI Model by C-L-V | AlphaNeural AI

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C-L-V/
PsyDefDetect_bert-base-uncased_unmerged_lr-4

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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_unmerged_lr-4

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: 2.2184
Accuracy: 0.5147
Macro F1: 0.0755
Weighted F1: 0.3498
Macro Precision: 0.0572
Macro Recall: 0.1111

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: 0.0002
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
2.2482	1.0	187	2.2192	0.5147	0.0755	0.3498	0.0572	0.1111
2.2175	2.0	374	2.2003	0.5147	0.0755	0.3498	0.0572	0.1111
2.1808	3.0	561	2.2154	0.1528	0.0295	0.0405	0.0170	0.1111

Framework versions

Transformers 5.0.0
Pytorch 2.10.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2