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lifechart-bert-large-classifier-hptuning

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lifechart-bert-large-classifier-hptuning

This model is a fine-tuned version of bert-large-uncased on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.8621
Macro F1: 0.7954
Precision: 0.7850
Recall: 0.8132

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: 3.051761556062339e-05
train_batch_size: 16
eval_batch_size: 16
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
lr_scheduler_warmup_ratio: 0.0655781666684222
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Macro F1	Precision	Recall
1.7088	1.0	821	0.8249	0.7430	0.7055	0.8019
0.5942	2.0	1642	0.7587	0.7776	0.7574	0.8110
0.2852	3.0	2463	0.8621	0.7954	0.7850	0.8132

Framework versions

Transformers 4.55.4
Pytorch 2.8.0+cu128
Datasets 4.0.0
Tokenizers 0.21.4

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Safetensors

Model size

335M params

Tensor type

F32

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Base model

google-bert/bert-large-uncased

Finetuned

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Evaluation results

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