bert_finetune_prompt_classification – AI Model by alexpaunoiu | AlphaNeural AI

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alexpaunoiu/
bert_finetune_prompt_classification

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text-classification

generated_from_trainer

google-bert/bert-base-uncased

autotrain_compatible

endpoints_compatible

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bert_finetune_prompt_classification

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: 0.1537

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: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 30
num_epochs: 12

Training results

Training Loss	Epoch	Step	Validation Loss
0.945	1.0	33	0.9316
0.5897	1.99	66	0.3983
0.2354	2.99	99	0.2213
0.237	3.98	132	0.1955
0.2126	4.98	165	0.1485
0.124	5.98	198	0.1412
0.1857	6.97	231	0.1540
0.108	8.0	265	0.1602
0.0801	9.0	298	0.1561
0.0421	9.99	331	0.1430
0.015	10.99	364	0.1480
0.0113	11.95	396	0.1537

Framework versions

Transformers 4.34.1
Pytorch 2.0.0+cu117
Datasets 2.14.5
Tokenizers 0.14.1