results_pipeline1 – AI Model by zhizhi188 | AlphaNeural AI

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zhizhi188/
results_pipeline1

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text-classification

generated_from_trainer

distilbert/distilbert-base-uncased

text-embeddings-inference

endpoints_compatible

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results_pipeline1

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

Loss: 0.0474
F1 Micro: 0.9912
F1 Macro: 0.9759
Precision Micro: 1.0
Recall Micro: 0.9825

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: 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
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	F1 Micro	F1 Macro	Precision Micro	Recall Micro
0.3390	1.0	191	0.1619	0.9259	0.8508	0.9804	0.8772
0.1922	2.0	382	0.0889	0.9689	0.9313	0.9820	0.9561
0.1355	3.0	573	0.0630	0.9823	0.9620	0.9911	0.9737
0.0937	4.0	764	0.0474	0.9912	0.9759	1.0	0.9825
0.0826	5.0	955	0.0420	0.9912	0.9759	1.0	0.9825

Framework versions

Transformers 5.0.0
Pytorch 2.10.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2