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ASAP_FineTuningBERT_AugV5_k5_task1_organization_fold3

Text Classification

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ASAP_FineTuningBERT_AugV5_k5_task1_organization_fold3

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: 9.9667
Qwk: 0.0065
Mse: 9.9660
Rmse: 3.1569

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: 64
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Qwk	Mse	Rmse
No log	0.5	2	10.8576	0.0170	10.8568	3.2950
No log	1.0	4	9.9667	0.0065	9.9660	3.1569

Framework versions

Transformers 4.44.2
Pytorch 2.4.1+cu121
Datasets 3.2.0
Tokenizers 0.19.1

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Safetensors

Model size

0.1B params

Tensor type

F32

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google-bert/bert-base-uncased

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