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amitca71/
bert-base-parsbert-uncased-farsi_syntetic_data_openai4omini

Name: bert-base-parsbert-uncased-farsi_syntetic_data_openai4omini
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bert-base-parsbert-uncased-farsi_syntetic_data_openai4omini

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

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The following hyperparameters were used during training:

learning_rate: 1e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 32
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: 0.1
num_epochs: 15
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall	F1 Class 0	F1 Class 1
0.1448	1.0	844	0.0044	0.9994	0.9994	0.9994	0.9994	0.9994	0.9994
0.0018	2.0	1688	0.0056	0.9991	0.9991	0.9991	0.9991	0.9991	0.9991
0.0013	3.0	2532	0.0050	0.9994	0.9994	0.9994	0.9994	0.9994	0.9994
0.0004	4.0	3376	0.0026	0.9997	0.9997	0.9997	0.9997	0.9997	0.9997
0.0018	5.0	4220	0.0020	0.9994	0.9994	0.9994	0.9994	0.9994	0.9994
0.0006	6.0	5064	0.0009	0.9997	0.9997	0.9997	0.9997	0.9997	0.9997
0.0	7.0	5908	0.0003	0.9997	0.9997	0.9997	0.9997	0.9997	0.9997
0.0	8.0	6752	0.0001	1.0	1.0	1.0	1.0	1.0	1.0
0.0004	9.0	7596	0.0008	0.9997	0.9997	0.9997	0.9997	0.9997	0.9997
0.0	10.0	8440	0.0013	0.9997	0.9997	0.9997	0.9997	0.9997	0.9997
0.0	11.0	9284	0.0016	0.9997	0.9997	0.9997	0.9997	0.9997	0.9997
0.0	12.0	10128	0.0014	0.9997	0.9997	0.9997	0.9997	0.9997	0.9997
0.0	13.0	10972	0.0016	0.9997	0.9997	0.9997	0.9997	0.9997	0.9997
0.0	14.0	11816	0.0023	0.9997	0.9997	0.9997	0.9997	0.9997	0.9997
0.0	15.0	12660	0.0023	0.9997	0.9997	0.9997	0.9997	0.9997	0.9997