conplag2_unixcoder_ep30_bs16_lr2e-05_l512_s42_ppy_loss – AI Model by buelfhood | AlphaNeural AI

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buelfhood/
conplag2_unixcoder_ep30_bs16_lr2e-05_l512_s42_ppy_loss

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text-classification

generated_from_trainer

microsoft/unixcoder-base-nine

text-embeddings-inference

endpoints_compatible

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conplag2_unixcoder_ep30_bs16_lr2e-05_l512_s42_ppy_loss

This model is a fine-tuned version of microsoft/unixcoder-base-nine on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.3859
Accuracy: 0.8613
Recall: 0.7105
Precision: 0.7714
F1: 0.7397
F Beta Score: 0.7282

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 with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Recall	Precision	F1	F Beta Score
0.5691	1.0	40	0.4540	0.8029	0.6053	0.6571	0.6301	0.6203
0.5595	2.0	80	0.3859	0.8613	0.7105	0.7714	0.7397	0.7282
0.4013	3.0	120	0.4988	0.8686	0.6316	0.8571	0.7273	0.6872
0.1997	4.0	160	0.5323	0.8905	0.6316	0.96	0.7619	0.7059
0.0899	5.0	200	0.7567	0.8686	0.6842	0.8125	0.7429	0.7191

Framework versions

Transformers 4.51.3
Pytorch 2.8.0+cu128
Datasets 3.1.0
Tokenizers 0.21.4